Associate Professor Qi Wu
Associate Prof/Reader
School of Computer and Mathematical Sciences
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD, but is currently at capacity - email supervisor to discuss availability.
Dr Qi Wu is currently an Associate Professor in the University of Adelaide and he was an ARC Senior Research Associate in the Australian Centre for Robotic Vision (ACRV) in the University of Adelaide, Australia. Before that, he works as a Postdoc Researcher in the Australian Centre for Visual Technologies (ACVT). He received an MSc in Global Computing and Media Technology, a PhD in Computer Science from the University of Bath (United Kingdom), in 2011 and 2015. His research interests include cross-depictive style object modelling, object detection and Vision-to-Language problems. He is especially interested in the problem of Image Captioning and Visual Question Answering. His image captioning model produced the best result in the Microsoft COCO Image Captioning Challenges in the last year and his VQA model is the current state-of-the-art in the area. His work has been published in prestigious journals and conferences such as TPAMI, CVPR, ICCV and ECCV.
My research interests are mainly in computer vision and machine learning. My previous research projects include modeling visual objects regardless of depictive styles and image understanding using contextual cues. I am currently leading a small team at the Adelaide to research on the topic of Vision-and-Language.
I have been in the computer vision filed for nearly 10 years and I have a strong track record in this field. Currently, I am working on the vision to language problem and I am especially an expert in the image captioning and visual question answering (VQA). In 2015, my image captioning model and VQA model achieved the leading performance in the Microsoft COCO Image Captioning Challenges and VQA Challenges. I have published several papers in the top journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Signal Processing Magazine (SPM), Computer Vision and Image Understanding (CVIU). I also have published several papers on the top conference, such as International Joint Conference on Artificial Intelligence (IJCAI), AAAI, The Conference on Computer Vision and Pattern Recognition (CVPR) and the European Conference on Computer Vision (ECCV), and so on.
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Appointments
Date Position Institution name 2023 - ongoing Associate Professor University of Adelaide 2018 - 2022 Senior Lecturer University of Adelaide, Adelaide 2017 - 2018 ARC Senior Research Associate Australia Centre for Robotic Vision, University of Adelaide 2015 - 2017 Senior Research Associate University of Adelaide 2014 - ongoing Research Intern Lenovo 2011 - 2015 PhD University of Bath -
Language Competencies
Language Competency Chinese (Mandarin) Can read, write, speak, understand spoken and peer review English Can read, write, speak, understand spoken and peer review -
Education
Date Institution name Country Title 2011 - 2015 University of Bath United Kingdom PhD 2010 - 2011 University of Bath United Kingdom MSc 2006 - 2010 China Jiliang University China BSc -
Research Interests
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Journals
Year Citation 2023 Suo, W., Sun, M., Wang, P., Zhang, Y., & Wu, Q. (2023). Rethinking and Improving Feature Pyramids for One-Stage Referring Expression Comprehension. IEEE Transactions on Image Processing, 32, 854-864.
2023 Qiao, Y., Qi, Y., Hong, Y., Yu, Z., Wang, P., & Wu, Q. (2023). HOP+: History-Enhanced and Order-Aware Pre-Training for Vision-and-Language Navigation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-14.
2023 Wang, Z., Byrnes, O., Wang, H., Sun, R., Ma, C., Chen, H., . . . Xue, M. (2023). Data Hiding With Deep Learning: A Survey Unifying Digital Watermarking and Steganography. IEEE Transactions on Computational Social Systems, 1-15.
2022 Ling, L., Wu, Q., Huang, K., Wang, Y., & Wang, C. (2022). A Lightweight Bearing Fault Diagnosis Method Based on Multi-Channel Depthwise Separable Convolutional Neural Network. Electronics (Switzerland), 11(24), 4110.
Scopus22022 Wang, H., Chen, H., Wu, Q., Ma, C., & Li, Y. (2022). Multi-Intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baseline. IEEE Open Journal of Intelligent Transportation Systems, 3, 126-136.
Scopus12022 He, M., Du, W., Wen, Z., Du, Q., Xie, Y., & Wu, Q. (2022). Multi-Granularity Aggregation Transformer for Joint Video-Audio-Text Representation Learning. IEEE Transactions on Circuits and Systems for Video Technology, 1.
2022 Sun, M., Suo, W., Wang, P., Zhang, Y., & Wu, Q. (2022). A proposal-free one-stage framework for referring expression comprehension and generation via dense cross-attention. IEEE Transactions on Multimedia, 1.
Scopus52022 Deng, C., Wu, Q., Wu, Q., Hu, F., Lyu, F., & Tan, M. (2022). Visual Grounding Via Accumulated Attention. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(3), 1670-1684.
Scopus2 WoS12022 Parvaneh, A., Abbasnejad, E., Wu, Q., Shi, Q., & Van Den Hengel, A. (2022). Show, price and negotiate: a hierarchical attention recurrent visual negotiator. IEEE Transactions on Multimedia, 24, 1426-1434.
2022 Sun, Z., Liu, H., Wang, Q., Zhou, T., Wu, Q., & Tang, Z. (2022). Co-LDL: A Co-training-based Label Distribution Learning Method for Tackling Label Noise. IEEE Transactions on Multimedia, 24, 1093-1104.
Scopus10 WoS62021 Yu, J., Jiang, X., Qin, Z., Zhang, W., Hu, Y., & Wu, Q. (2021). Learning Dual Encoding Model for Adaptive Visual Understanding in Visual Dialogue. IEEE TRANSACTIONS ON IMAGE PROCESSING, 30, 220-233.
Scopus9 WoS72021 Wang, Y., Qi, Y., Yao, H., Gong, D., & Wu, Q. (2021). Image editing with varying intensities of processing. Computer Vision and Image Understanding, 211, 1-13.
Scopus3 WoS42021 Zhang, W., Ma, C., Wu, Q., & Yang, X. (2021). Language-guided Navigation via Cross-Modal Grounding and Alternate Adversarial Learning. IEEE Transactions on Circuits and Systems for Video Technology, 31(9), 3469-3481.
Scopus11 WoS102021 Zhang, C., Wang, Q., Xie, G., Wu, Q., Shen, F., & Tang, Z. (2021). Robust Learning from Noisy Web Images via Data Purification for Fine-Grained Recognition. IEEE Transactions on Multimedia, 24, 1.
Scopus5 WoS12020 Gao, C., Zhu, Q., Wang, P., Li, H., Liu, Y., Van den Hengel, A., & Wu, Q. (2020). Structured Multimodal Attentions for TextVQA. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(8), 1.
Scopus42020 Chen, Q., Wu, Q., Chen, J., Wu, Q., Van Den Hengel, A., & Tan, M. (2020). Scripted Video Generation with a Bottom-Up Generative Adversarial Network. IEEE Transactions on Image Processing, 29, 7454-7467.
Scopus9 WoS52020 Qiao, Y., Deng, C., & Wu, Q. (2020). Referring expression comprehension: a survey of methods and datasets. IEEE Transactions on Multimedia, 23, 4426-4440.
Scopus8 WoS42020 Yu, J., Zhang, W., Lu, Y., Qin, Z., Hu, Y., Tan, J., & Wu, Q. (2020). Reasoning on the Relation: Enhancing Visual Representation for Visual Question Answering and Cross-Modal Retrieval. IEEE Transactions on Multimedia, 22(12), 3196-3209.
Scopus34 WoS192020 Huang, Y., Wu, Q., Wang, W., & Wang, L. (2020). Image and Sentence Matching via Semantic Concepts and Order Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(3), 636-650.
Scopus18 WoS132019 Liu, W., Li, Y., & Wu, Q. (2019). An Attribute-Based High-Level Image Representation for Scene Classification. IEEE Access, 7, 4629-4640.
Scopus3 WoS12019 Lyu, F., Wu, Q., Hu, F., Wu, Q., & Tan, M. (2019). Attend and Imagine: Multi-Label Image Classification with Visual Attention and Recurrent Neural Networks. IEEE Transactions on Multimedia, 21(8), 1971-1981.
Scopus40 WoS342019 Zhang, J., Wu, Q., Zhang, J., Shen, C., Lu, J., & Wu, Q. (2019). Heritage image annotation via collective knowledge. Pattern Recognition, 93, 204-214.
Scopus5 WoS52019 Zhang, J., Xie, Y., Wu, Q., & Xia, Y. (2019). Medical image classification using synergic deep learning. Medical Image Analysis, 54, 10-19.
Scopus202 WoS134 Europe PMC272018 Wu, Q., Shen, C., Wang, P., Dick, A., & van den Hengel, A. (2018). Image captioning and visual question answering based on attributes and external knowledge. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(6), 1367-1381.
Scopus233 WoS182 Europe PMC72018 Zhang, J., Wu, Q., Shen, C., Zhang, J., & Lu, J. (2018). Multilabel image classification with regional latent semantic dependencies. IEEE Transactions on Multimedia, 20(10), 2801-2813.
Scopus119 WoS462017 Teney, D., Wu, Q., & Van Den Hengel, A. (2017). Visual Question Answering: a tutorial. IEEE Signal Processing Magazine, 34(6), 63-75.
Scopus25 WoS172017 Wang, P., Wu, Q., Shen, C., Dick, A., & Van Den Hengel, A. (2017). FVQA: fact-based Visual Question Answering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(10), 2413-2427.
Scopus185 WoS147 Europe PMC52017 Wu, Q., Teney, D., Wang, P., Shen, C., Dick, A., & van den Hengel, A. (2017). Visual question answering: a survey of methods and datasets. Computer Vision and Image Understanding, 163, 21-40.
Scopus185 WoS1302015 Hall, P., Cai, H., Wu, Q., & Corradi, T. (2015). Cross-depiction problem: recognition and synthesis of photographs and artwork. Computational Visual Media, 1(2), 91-103.
Scopus22- Zhuang, B., Wu, Q., Shen, C., Reid, I., & Hengel, A. V. D. (n.d.). Care about you: towards large-scale human-centric visual relationship
detection.- Moghaddam, M. K., Abbasnejad, E., Wu, Q., Shi, J., & Hengel, A. V. D. (n.d.). Learning for Visual Navigation by Imagining the Success. - Manchin, A., Sherrah, J., Wu, Q., & Hengel, A. V. D. (n.d.). Program Generation from Diverse Video Demonstrations. -
Books
Year Citation 2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Visual Question Answering. Springer Nature Singapore.
2020 Garg, S., Sünderhauf, N., Dayoub, F., Morrison, D., Cosgun, A., Carneiro, G., . . . Milford, M. (2020). Semantics for Robotic Mapping, Perception and Interaction: A Survey (Vol. 8). United States: Now Publishers.
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Book Chapters
Year Citation 2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Video Representation Learning. In Advances in Computer Vision and Pattern Recognition (pp. 111-117). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Vision-and-Language Pretraining for VQA. In Advances in Computer Vision and Pattern Recognition (pp. 91-107). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Text-Based VQA. In Advances in Computer Vision and Pattern Recognition (pp. 177-187). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Deep Learning Basics. In Advances in Computer Vision and Pattern Recognition (pp. 15-26). Springer Nature Singapore.
Scopus12022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Summary and Outlook. In Advances in Computer Vision and Pattern Recognition (pp. 233-236). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Knowledge-Based VQA. In Advances in Computer Vision and Pattern Recognition (pp. 73-90). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Medical VQA. In Advances in Computer Vision and Pattern Recognition (pp. 165-176). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Question Answering (QA) Basics. In Advances in Computer Vision and Pattern Recognition (pp. 27-31). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Visual Dialogue. In Advances in Computer Vision and Pattern Recognition (pp. 199-218). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Referring Expression Comprehension. In Advances in Computer Vision and Pattern Recognition (pp. 219-230). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Classical Visual Question Answering. In Advances in Computer Vision and Pattern Recognition (pp. 35-72). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Advanced Models for Video Question Answering. In Advances in Computer Vision and Pattern Recognition (pp. 135-143). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Video Question Answering. In Advances in Computer Vision and Pattern Recognition (pp. 119-133). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Visual Question Generation. In Advances in Computer Vision and Pattern Recognition (pp. 189-197). Springer Nature Singapore.
2022 Wu, Q., Wang, P., Wang, X., He, X., & Zhu, W. (2022). Embodied VQA. In Advances in Computer Vision and Pattern Recognition (pp. 147-164). Springer Nature Singapore.
2015 Brown-Grant, R. (2015). Introduction. In R. BrownGrant, A. D. Hedeman, & B. Ribemont (Eds.), Advances in Computer Vision and Pattern Recognition (pp. 1-13). ROUTLEDGE.
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Conference Papers
Year Citation 2023 Luo, Z., Li, Y., Yu, L., Wu, Q., Wen, Z., Fan, H., & Liu, S. (2023). Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13802 LNCS (pp. 561-572). Springer Nature Switzerland.
2022 Jing, C., Jia, Y., Wu, Y., Li, C., & Wu, Q. (2022). Learning the Dynamics of Visual Relational Reasoning via Reinforced Path Routing. In Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 Vol. 36 (pp. 951-959). ELECTR NETWORK: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Scopus12022 Kazemi Moghaddam, M., Abbasnejad, E., Wu, Q., Qinfeng Shi, J., & Van Den Hengel, A. (2022). ForeSI: Success-Aware Visual Navigation Agent. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2022) (pp. 3401-3410). Online: IEEE.
Scopus12022 Qi, Y., Pan, Z., Hong, Y., Yang, M. H., Van Den Hengel, A., & Wu, Q. (2022). The Road to Know-Where: An Object-and-Room Informed Sequential BERT for Indoor Vision-Language Navigation. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2021) (pp. 1635-1644). online: IEEE.
Scopus142022 Suo, W., Sun, M., Niu, K., Gao, Y., Wang, P., Zhang, Y., & Wu, Q. (2022). A Simple and Robust Correlation Filtering Method for Text-Based Person Search. In S. Avidan, G. Brostow, M. Cisse, G. M. Farinella, & T. Hassner (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13695 LNCS (pp. 726-742). Tel Aviv, ISRAEL: SPRINGER INTERNATIONAL PUBLISHING AG.
2022 Gu, J., Stefani, E., Wu, Q., Thomason, J., & Wang, X. E. (2022). Vision-and-Language Navigation: A Survey of Tasks, Methods, and Future Directions. In Proceedings of the Annual Meeting of the Association for Computational Linguistics Vol. 1 (pp. 7606-7623). Dublin, IRELAND: ASSOC COMPUTATIONAL LINGUISTICS-ACL.
Scopus8 WoS32022 Zhu, W., Qi, Y., Narayana, P., Sone, K., Basu, S., Wang, E. X., . . . Wang, W. Y. (2022). Diagnosing Vision-and-Language Navigation: What Really Matters. In NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 5981-5993). Seattle, WA: ASSOC COMPUTATIONAL LINGUISTICS-ACL.
Scopus12022 Bhat, G., Danelljan, M., Timofte, R., Cao, Y., Cao, Y., Chen, M., . . . Zuo, W. (2022). NTIRE 2022 Burst Super-Resolution Challenge. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2022-June (pp. 1040-1060). Online: IEEE.
Scopus152022 Chen, Q., Tan, M., Qi, Y., Zhou, J., Li, Y., & Wu, Q. (2022). V2C: Visual Voice Cloning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, 2022) Vol. 2022-June (pp. 21210-21219). New Orleans, Louisiana: IEEE.
2022 Jing, C., Jia, Y., Wu, Y., Liu, X., & Wu, Q. (2022). Maintaining Reasoning Consistency in Compositional Visual Question Answering. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 5089-5098). New Orleans, LA: IEEE COMPUTER SOC.
2022 Hong, Y., Wang, Z., Wu, Q., & Gould, S. (2022). Bridging the Gap Between Learning in Discrete and Continuous Environments for Vision-and-Language Navigation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 15418-15428). New Orleans, LA: IEEE COMPUTER SOC.
Scopus12022 Xie, Y., Zhang, J., Xia, Y., & Wu, Q. (2022). UniMiSS: Universal Medical Self-supervised Learning via Breaking Dimensionality Barrier. In Proceedings, Part XXI of the 17th European Conference on Computer Vision (ECCV 2022), as published in Lecture Notes in Computer Science Vol. 13681 LNCS (pp. 558-575). Tel Aviv: Springer.
Scopus12022 Ding, Y., Yu, J., Liu, B., Hu, Y., Cui, M., & Wu, Q. (2022). MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question Answering. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 5079-5088). New Orleans, LA: IEEE COMPUTER SOC.
Scopus42022 Qiao, Y., Qi, Y., Hong, Y., Yu, Z., Wang, P., & Wu, Q. (2022). HOP: History-and-Order Aware Pretraining for Vision-and-Language Navigation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 15397-15406). New Orleans, LA: IEEE COMPUTER SOC.
Scopus22022 Chen, C., Hu, Z., Jin, S., Xiao, L., Hu, M., Wu, Q., . . . Zou, M. (2022). Classification of COVID-19 in CT Scans Using Image Smoothing and Improved Deep Residual Network. In Artificial Intelligence First CAAI International Conference, CICAI 2021, Hangzhou, China, June 5–6, 2021, Proceedings, Part I Vol. 13069 LNAI (pp. 89-100). Switzerland: Springer.
2021 Yao, Y., Chen, T., Xie, G. S., Zhang, C., Shen, F., Wu, Q., . . . Zhang, J. (2021). Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2623-2632). online: IEEE.
Scopus74 WoS552021 Yao, Y., Sun, Z., Zhang, C., Shen, F., Wu, Q., Zhang, J., & Tang, Z. (2021). Jo-SRC: A Contrastive Approach for Combating Noisy Labels. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 5188-5197). online: IEEE.
Scopus35 WoS232021 Deng, C., Chen, S., Chen, D., He, Y., & Wu, Q. (2021). Sketch, ground, and refine: top-down dense video captioning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2021) (pp. 234-243). online: IEEE.
Scopus18 WoS72021 Hong, Y., Wu, Q., Qi, Y., Rodriguez Opazo, C., & Gould, S. (2021). VLN↻BERT: A Recurrent Vision-and-Language BERT for Navigation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 1643-1653). online: IEEE.
Scopus43 WoS172021 Xu, G., Niu, S., Tan, M., Luo, Y., Du, Q., & Wu, Q. (2021). Towards Accurate Text-based Image Captioning with Content Diversity Exploration. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 12632-12641). online: IEEE.
Scopus20 WoS92021 Gao, C., Chen, J., Liu, S., Wang, L., Zhang, Q., & Wu, Q. (2021). Room-and-Object Aware Knowledge Reasoning for Remote Embodied Referring Expression. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 3063-3072). online: IEEE COMPUTER SOC.
Scopus20 WoS82021 Wu, Q., Wu, C. J., Zhu, Y., & Joo, J. (2021). Communicative Learning with Natural Gestures for Embodied Navigation Agents with Human-in-the-Scene. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4095-4102). online: IEEE.
Scopus32021 Yu, J., Chai, Y., Wang, Y., Hu, Y., & Wu, Q. (2021). CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation. In IJCAI International Joint Conference on Artificial Intelligence (pp. 1274-1280). online: International Joint Conferences on Artificial Intelligence.
Scopus102021 Suo, W., Sun, M., Wang, P., & Wu, Q. (2021). Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention. In IJCAI International Joint Conference on Artificial Intelligence (pp. 1032-1038). online: International Joint Conferences on Artificial Intelligence.
Scopus22021 Gao, C., Zhu, Q., Wang, P., & Wu, Q. (2021). Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) (pp. 664-670). United States: International Joint Conferences on Artificial Intelligence.
Scopus22021 An, D., Qi, Y., Huang, Y., Wu, Q., Wang, L., & Tan, T. (2021). Neighbor-view Enhanced Model for Vision and Language Navigation. In MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia (pp. 5101-5109). virtual online: ACM.
Scopus62021 Qiao, Y., Chen, Q., Deng, C., DIng, N., Qi, Y., Tan, M., . . . Wu, Q. (2021). R-GAN: Exploring Human-like Way for Reasonable Text-to-Image Synthesis via Generative Adversarial Networks. In MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia (pp. 2085-2093). New York, NY, United States: Association for Computing Machinery.
Scopus32021 Wen, Z., Xu, G., Tan, M., Wu, Q., & Wu, Q. (2021). Debiased Visual Question Answering from Feature and Sample Perspectives. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. Wortman Vaughan (Eds.), Advances in Neural Information Processing Systems 34 Vol. 5 (pp. 3784-3796). Online: Neural Information Processing Systems Foundation, Inc (NeurIPS).
Scopus32021 He, K., Huang, Y., Wu, Q., Yang, J., An, D., Sima, S., & Wang, L. (2021). Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision. In Advances in Neural Information Processing Systems Vol. 2 (pp. 652-663). ELECTR NETWORK: NEURAL INFORMATION PROCESSING SYSTEMS (NIPS).
Scopus32021 Kazemi Moghaddam, M., Wu, Q., Abbasnejad, E., & Shi, J. (2021). Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2021) (pp. 3732-3741). online: IEEE.
Scopus8 WoS82021 Zheng, Y., Wen, Z., Tan, M., Zeng, R., Chen, Q., Wang, Y., & Wu, Q. (2021). Modular graph attention network for complex visual relational reasoning. In Proceedings of the 15th Asian Conference on Computer Vision (ACCV 2020), as published in Lecture Notes in Computer Science Vol. 12627 (pp. 137-153). Cham, Switzerland: Springer.
Scopus12021 Zhu, Q., Gao, C., Wang, P., & Wu, Q. (2021). Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps. In THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE Vol. 35 (pp. 3608-3615). ELECTR NETWORK: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Scopus13 WoS62021 Wang, Z., Bao, R., Wu, Q., & Liu, S. (2021). Confidence-aware Non-repetitive Multimodal Transformers for TextCaps. In THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE Vol. 35 (pp. 2835-2843). ELECTR NETWORK: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Scopus7 WoS32021 Liu, L., He, M., Xu, G., Tan, M., & Wu, Q. (2021). How to Train Your Agent to Read and Write. In THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE Vol. 35 (pp. 13397-13405). Online: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
WoS12021 Wu, Q., Qin, M., Song, J., & Liu, L. (2021). An improved method of low light image enhancement based on retinex. In 2021 6th International Conference on Image, Vision and Computing, ICIVC 2021 (pp. 233-241). online: IEEE.
Scopus32020 Hong, Y., Rodriguez Opazo, C., Wu, Q., & Gould, S. (2020). Sub-Instruction Aware Vision-and-Language Navigation. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 3360-3376). virtual online: Association for Computational Linguistics.
Scopus15 WoS72020 Jiang, X., Yu, J., Qin, Z., Zhuang, Y., Zhang, X., Hu, Y., & Wu, Q. (2020). DualVD: An adaptive dual encoding model for deep visual understanding in visual dialogue. In AAAI 2020 - 34th AAAI Conference on Artificial Intelligence Vol. 34 (pp. 11125-11132). online: AAAI.
Scopus38 WoS182020 Jing, C., Wu, Y., Zhang, X., Jia, Y., & Wu, Q. (2020). Overcoming language priors in VQA via decomposed linguistic representations. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20) Vol. 34 (pp. 11181-11188). online: AAAI.
Scopus37 WoS182020 Zhang, C., Yao, Y., Shu, X., Li, Z., Tang, Z., & Wu, Q. (2020). Data-driven Meta-set Based Fine-Grained Visual Recognition. In MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia (pp. 2372-2381). online: ACM.
Scopus16 WoS22020 Wang, P., Liu, D., Li, H., & Wu, Q. (2020). Give Me Something to Eat: Referring Expression Comprehension with Commonsense Knowledge. In MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia (pp. 28-36). online: ACM.
Scopus102020 Jing, C., Wu, Y., Pei, M., Hu, Y., Jia, Y., & Wu, Q. (2020). Visual-Semantic Graph Matching for Visual Grounding. In MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia (pp. 4041-4050). online: ACM.
Scopus122020 Liu, F., Xu, G., Wu, Q., Du, Q., Jia, W., & Tan, M. (2020). Cascade Reasoning Network for Text-based Visual Question Answering. In MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia (pp. 4060-4069). online: ACM.
Scopus22 WoS22020 Hong, Y., Rodriguez-Opazo, C., Qi, Y., Wu, Q., & Gould, S. (2020). Language and visual entity relationship graph for agent navigation. In Advances in Neural Information Processing Systems Vol. 2020-December (pp. 1-12). online: NIPS.
Scopus282020 Liao, Z., Liu, L., Wu, Q., Teney, D., Shen, C., Van Den Hengel, A., & Verjans, J. (2020). Medical data inquiry using a question answering model. In Proceedings: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020) Vol. 2020-April (pp. 1490-1493). online: IEEE.
Scopus5 WoS32020 Wang, H., Wu, Q., & Shen, C. (2020). Soft Expert Reward Learning for Vision-and-Language Navigation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12354 LNCS (pp. 126-141). Switzerland: Springer Nature.
Scopus132020 Tang, R., Ma, C., Zhang, W. E., Wu, Q., & Yang, X. (2020). Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12364 LNCS (pp. 437-453). Switzerland: Springer International Publishing.
Scopus92020 Deng, C., Ding, N., Tan, M., & Wu, Q. (2020). Length-Controllable Image Captioning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12358 LNCS (pp. 712-729). Switzerland: Springer International Publishing.
Scopus142020 Qi, Y., Pan, Z., Zhang, S., van den Hengel, A., & Wu, Q. (2020). Object-and-Action Aware Model for Visual Language Navigation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12355 LNCS (pp. 303-317). Switzerland: Springer International Publishing.
Scopus192020 Jiang, X., Yu, J., Sun, Y., Qin, Z., Zhu, Z., Hu, Y., & Wu, Q. (2020). DAM: Deliberation, abandon and memory networks for generating detailed and non-repetitive responses in visual dialogue. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2021-January (pp. 687-693). online: AAAI Press.
Scopus4 WoS12020 Zhu, Z., Yu, J., Wang, Y., Sun, Y., Hu, Y., & Wu, Q. (2020). Mucko: Multi-layer cross-modal knowledge reasoning for fact-based visual question answering. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2021-January (pp. 1097-1103). online: AAAI Press.
Scopus31 WoS282020 Chen, Z., Wang, P., Ma, L., Wong, K. Y. K., & Wu, Q. (2020). Cops-Ref: A New Dataset and Task on Compositional Referring Expression Comprehension. In Proceedings of the 2020 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 10083-10092). online: IEEE.
Scopus192020 Qi, Y., Wu, Q., Anderson, P., Wang, X., Wang, W. Y., Shen, C., & Van Den Hengel, A. (2020). Reverie: Remote embodied visual referring expression in real indoor environments. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 9979-9988). online: IEEE.
Scopus712020 Liao, Z., Wu, Q., Shen, C., Van Den Hengel, A., & Verjans, J. (2020). AIML at VQA-Med 2020: Knowledge inference via a skeleton-based sentence mapping approach for medical domain visual question answering. In L. Cappellato, C. Eickhoff, N. Ferro, & A. Névéol (Eds.), Proceedings of the 11th International Conference of the CLEF Initiative (CLEF 2020), as published in CEUR Workshop Proceedings Vol. 2696 (pp. 1-14). online: CEUR-WS.
Scopus12020 Abbasnejad, M., Abbasnejad, I., Wu, Q., Shi, Q., & Van Den Hengel, A. (2020). Gold seeker: Information gain from policy distributions for goal-oriented vision-and-langauge reasoning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 13447-13456). online: IEEE.
Scopus22020 Chen, S., Jin, Q., Wang, P., & Wu, Q. (2020). Say as you wish: Fine-grained control of image caption generation with abstract scene graphs. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 9959-9968). online: IEEE.
Scopus1042020 Chen, S., Zhao, Y., Jin, Q., & Wu, Q. (2020). Fine-grained video-text retrieval with hierarchical graph reasoning. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 10635-10644). online: IEEE.
Scopus1252020 Chen, Q., Wu, Q., Tang, R., Wang, Y., Wang, S., & Tan, M. (2020). Intelligent home 3D: Automatic 3D-house design from linguistic descriptions only. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 12622-12631). online: IEEE.
Scopus152019 Duan, X., Wu, Q., Gan, C., Zhang, Y., Huang, W., Van Den Hengel, A., & Zhu, W. (2019). Watch, reason and code: Learning to represent videos using program. In Proceedings of the 27th ACM International Conference on Multimedia (ACM Multimedia 2019), MM '19 (pp. 1543-1551). online: Association for Computing Machinery.
Scopus3 WoS12019 Abbasnejad, E., Wu, Q., Shi, Q., & Van Den Hengel, A. (2019). What's to know? uncertainty as a guide to asking goal-oriented questions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 4150-4159). online: IEEE.
Scopus12 WoS62019 Zhang, J., Wu, Q., Zhang, J., Shen, C., & Lu, J. (2019). Mind your neighbours: Image annotation with metadata neighbourhood graph co-attention networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 2951-2959). online: IEEE.
Scopus14 WoS82019 Wang, P., Wu, Q., Cao, J., Shen, C., Gao, L., & Hengel, A. V. D. (2019). Neighbourhood watch: Referring expression comprehension via language-guided graph attention networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 1960-1968). online: IEEE.
Scopus132 WoS822018 Cao, I., Guo, Y., Wu, Q., Shen, C., Huang, J., & Tan, M. (2018). Adversarial learning with local coordinate coding. In 35th International Conference on Machine Learning, ICML 2018 Vol. 2 (pp. 1104-1117). online: PMLR.
Scopus18 WoS32018 Zhuang, Z., Tan, M., Zhuang, B., Liu, J., Guo, Y., Wu, Q., . . . Zhu, J. (2018). Discrimination-aware Channel Pruning for Deep Neural Networks. In Advances in Neural Information Processing Systems Vol. 2018-December (pp. 875-886). online: NIPS.
Scopus301 WoS672018 Zhang, J., Zhang, J., Wu, Q., Wu, Q., Xu, J., Lu, J., . . . Tang, Z. (2018). Historical image annotation by exploring the tag relevance. In Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017 (pp. 646-651). Nanjing, PEOPLES R CHINA: IEEE.
Scopus1 WoS12018 Zhuang, B., Wu, Q., Shen, C., Reid, I., & Van Den Hengel, A. (2018). HCVRD: A benchmark for large-scale human-centered visual relationship detection. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 7631-7638). New Orleans: Association for the Advancement of Artificial Intelligence.
Scopus26 WoS142018 Zhang, J., Wu, Q., Zhang, J., Shen, C., & Lu, J. (2018). Kill two birds with one stone: Weakly-supervised neural network for image annotation and tag refinement. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 7550-7557). New Orleans: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Scopus6 WoS42018 Wu, Q., Wang, P., Shen, C., Reid, I., & Hengel, A. (2018). Are you talking to me? Reasoned visual dialog generation through adversarial learning. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 6106-6115). Salt Lake City, UT: IEEE.
Scopus83 WoS512018 Deng, C., Wu, Q., Wu, Q., Hu, F., Lyu, F., & Tan, M. (2018). Visual Grounding via Accumulated Attention. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 7746-7755). online: IEEE.
Scopus116 WoS702018 Anderson, P., Das, A., & Wu, Q. (2018). Connecting language and vision to actions. In ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference Tutorial Abstracts (pp. 10-14). Melbourne: Association for Computational Linguistics.
2018 Huang, Y., Wu, Q., Song, C., & Wang, L. (2018). Learning Semantic Concepts and Order for Image and Sentence Matching. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 6163-6171). online: IEEE.
Scopus209 WoS1472018 Ma, C., Shen, C., Dick, A., Wu, Q., Wang, P., Van Den Hengel, A., & Reid, I. (2018). Visual Question Answering with memory-augmented network. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 6975-6984). Salt Lake City, Utah: IEEE.
Scopus66 WoS552018 Anderson, P., Wu, Q., Teney, D., Bruce, J., Johnson, M., Sünderhauf, N., . . . Hengel, A. V. D. (2018). Vision-and-language navigation: interpreting visually-grounded navigation instructions in real environments. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) Vol. abs/1711.07280 (pp. 3674-3683). Salt Lake City, UT: IEEE.
Scopus436 WoS10522018 Zhang, J., Xie, Y., Wu, Q., & Xia, Y. (2018). Skin lesion classification in dermoscopy images using synergic deep learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11071 LNCS (pp. 12-20). Switzerland: Springer.
Scopus34 WoS192018 Zhang, J., Wu, Q., Shen, C., Zhang, J., Lu, J., & van den Hengel, A. (2018). Goal-oriented visual question generation via intermediate rewards. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Computer Vision - ECCV 2018: Proceedings, Part V Vol. Lecture Notes in Computer Science; vol. 11209 (pp. 189-204). Munich: Springer.
Scopus11 WoS132018 Zhuang, B., Wu, Q., Shen, C., Reid, I., & van den Hengel, A. (2018). Parallel attention: a unified framework for visual object discovery through dialogs and queries. In Proceedings: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018) (pp. 4252-4261). Salt Lake City, UT: IEEE.
Scopus72 WoS412018 Wang, C., Zhao, R., Yang, X., & Wu, Q. (2018). Research of UAV Target Detection and Flight Control Based on Deep Learning. In 2018 International Conference on Artificial Intelligence and Big Data (ICAIBD) (pp. 170-174). online: IEEE.
WoS82017 Wang, Q., Chen, W., & Wu, Q. (2017). The research and application of an real-time embedded measurement and control system for the river discharge. In S. Li, Y. Dai, & Y. Cheng (Eds.), 2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE) (pp. 1295-1298). Changsha, PEOPLES R CHINA: IEEE.
2017 Wang, P., Wu, Q., Shen, C., & van den Hengel, A. (2017). The VQA-machine: learning how to use existing vision algorithms to answer new questions. In Proceedings: 30th IEEE Conference on Computer Vision and Pattern Recognition Vol. 2017-January (pp. 3909-3918). Honolulu: IEEE.
Scopus64 WoS342017 Wang, P., Wu, Q., Shen, C., Dick, A., & Van Den Hengel, A. (2017). Explicit knowledge-based reasoning for visual question answering. In C. Sierra (Ed.), Proceedings of the twenty-sixth International Joint Conference on Artificial Intelligence Vol. 0 (pp. 1290-1296). online: IJCAI.
Scopus90 WoS522016 Wu, Q., Wang, P., Shen, C., Dick, A., & Van Den Hengel, A. (2016). Ask me anything: free-form visual question answering based on knowledge from external sources. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 4622-4630). Las Vegas, NV: IEEE.
Scopus247 WoS1752016 Wu, Q., Shen, C., Liu, L., Dick, A., & Van Den Hengel, A. (2016). What value do explicit high level concepts have in vision to language problems?. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2016-December (pp. 203-212). Las Vegas, NV: IEEE.
Scopus368 WoS2692015 Cai, H., Wu, Q., & Hall, P. (2015). Beyond Photo-Domain Object Recognition: Benchmarks for the Cross-Depiction Problem. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2015-February (pp. 74-79). Santigo: IEEE.
Scopus1 WoS22015 Wu, Q., Chen, F. -C., & Huang, R. -Y. (2015). Detecting Temporal Community from Dynamic Heterogeneous Networks. In PROCEEDINGS OF 2015 4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2015) (pp. 610-613). Harbin, PEOPLES R CHINA: IEEE. 2014 Wu, Q., Cai, H., & Hall, P. (2014). Learning graphs to model visual objects across different depictive styles. In D. Fleet, T. Pajdia, B. Schiele, & T. Tuytelaars (Eds.), Proceedings of the 13th European Conference on Computer Vision Vol. VII (pp. 313-328). Zurich, Switzerland: Springer.
Scopus15 WoS52013 Wu, Q., & Hall, P. (2013). Modelling visual objects Invariant to depictive style. In T. Burghardt, D. Damen, W. Mayol-Cuevas, & M. Mirmehdi (Eds.), Proceedings of the British Machine Vision Conference (pp. 23.1-23.12). Bristol, UK: BMVA Press.
Scopus42012 Wu, Q., & Hall, P. (2012). Prime shapes in natural images. In R. Bowden, J. Collomosse, & K. Mikolajcczk (Eds.), Proceedings of the British Machine Vision Conference (pp. 45-1-45-12). Surrey, UK: BMVA Press.
Scopus4 WoS2
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MyIP-7370, CERA grants, Anton van den Hengel, Anthony Dick, Qi Wu, Answer Me Why：Explainability is Critical if We are to Trust Automated Decision Making, 98,000 AUD
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MyIP-7370, CERA grants, Anton van den Hengel, Anthony Dick, Qi Wu, Robust long-term Autonomous Navigation, 98,000 AUD
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Facebook’s Research and Academic Relations Program, Peter Anderson, Qi Wu, Damien Teney, Niko Sunderhauf, Stephen Gould, Anton van den Hengel, Treasure Hunt: Natural Language N
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Computer Vision
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Machine Learning
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Algorithms and Data Structure Analysis
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Research Methods
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Advanced Topics in Computer Science
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2023 Principal Supervisor Explainable Machine Learning via Examining the Vulnerability of Models Doctor of Philosophy Doctorate Full Time Mr Feng Chen 2023 Principal Supervisor Vision-and-Language in the Wild Doctor of Philosophy Doctorate Full Time Mr Zheng Yu 2022 Principal Supervisor Explainable Vision-and-Language Models Doctor of Philosophy Doctorate Full Time Mr Chaohan Wang 2022 Principal Supervisor Towards Robust and Efficient Referring Expression Comprehension Master of Philosophy Master Full Time Mr Chongyang Zhao 2022 Co-Supervisor MUDE: Mixed-reality Unified Development Environment for Context-Aware AI Automation Tasks Doctor of Philosophy Doctorate Full Time Miss Xiaoyan Wei 2022 Co-Supervisor Efficient Deep Learning on the Edge Doctor of Philosophy Doctorate Full Time Mr Xu Zhan 2022 Principal Supervisor Spatiotemporal Multimodal Learning in Embodied AI Doctor of Philosophy Doctorate Full Time Mr Gengze Zhou 2021 Principal Supervisor Generative Adversarial Networks (GANs) to Synthesize Images or Videos from Text. Doctor of Philosophy Doctorate Full Time Mr Qi Chen 2021 Co-Supervisor Recognizing Individual and Collective Activity Using Videos Doctor of Philosophy Doctorate Full Time Mr Bahram Mohammadi 2020 Principal Supervisor General Vision and Language Methods in Real Applications Doctor of Philosophy Doctorate Full Time Miss Yanyuan Qiao 2020 Principal Supervisor Towards Conversational Vision-Based Artificial Intelligence Doctor of Philosophy Doctorate Full Time Mr Chaorui Deng -
Past Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2019 - 2022 Co-Supervisor Towards Optimistic, Imaginative, and Harmonious Reinforcement Learning in
Single-Agent and Multi-Agent EnvironmentsDoctor of Philosophy Doctorate Full Time Mr Mahdi Kazemi Moghaddam 2018 - 2021 Co-Supervisor Fully Convolutional Instance-level Visual Recognition Doctor of Philosophy Doctorate Full Time Mr Zhi Tian 2018 - 2022 Co-Supervisor 3D Scene Reconstruction from A Monocular Image Doctor of Philosophy Doctorate Full Time Mr Wei Yin 2018 - 2021 Co-Supervisor Multi-modality Data Analysis Using Deep Reinforcement Learning Doctor of Philosophy Doctorate Full Time Mr Hu Wang 2018 - 2022 Co-Supervisor Efficient Deep Networks for Image Matting Doctor of Philosophy Doctorate Full Time Ms Yutong Dai 2017 - 2018 Co-Supervisor Text Detection and Recognition in Natural Scene Images Doctor of Philosophy Doctorate Full Time Mrs Hui Li
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