
Professor Simon Lucey
Director
Australian Institute for Machine Learning
Division of Research and Innovation
Eligible to supervise Masters and PhD - email supervisor to discuss availability.
Simon Lucey, Ph.D., is the Director of the Australian Institute for Machine Learning (AIML) at the University of Adelaide, the nation's largest machine learning research group. Previously, he previously held key positions at Carnegie Mellon University's Robotics Institute, autonomous vehicle company Argo AI, and CSIRO. He is a scientific advisor on the Temporary AI Expert Committee for the Department of Industry, Science and Resources.
Professor Lucey has received numerous career awards, including the 2024 AmCham Alliance Award for artificial intelligence and an Australian Research Council, Future Making Fellowship. With 11 patents in computer vision, over 300 publications, more than 19,700 citations, and an h-index of 62, his contributions to the field are widely recognised.
His research focuses on computer vision, machine learning, and robotics, drawing inspiration from pioneering AI researchers to uncover computational and mathematical models underlying visual perception.
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Journals
Year Citation 2025 Gordon, C., E. MacDonald, L., Saratchandran, H., & Lucey, S. (2025). D’OH: Decoder-Only Random Hypernetworks for Implicit Neural Representations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15478 LNCS, 128-147.
2025 Saratchandran, H., Wang, T. X., & Lucey, S. (2025). Weight Conditioning for Smooth Optimization of Neural Networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15143 LNCS, 310-325.
2025 Chng, S. F., Garg, R., Saratchandran, H., & Lucey, S. (2025). Invertible Neural Warp for NeRF. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15075 LNCS, 405-421.
2024 de la Perrelle, J. M., Hudson, R. J., Dolan, A., Jana, S., Pan, X., Andersson, M. R., . . . Kee, T. W. (2024). From light to hydrogen: the complete life cycle of free charges in photocatalytic nanoparticles. Sustainable Energy and Fuels, 8(14), 3145-3163.
Scopus32024 Saratchandran, H., Ramasinghe, S., & Lucey, S. (2024). From Activation to Initialization: Scaling Insights for Optimizing Neural Fields. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, abs/2403.19205, 413-422.
2024 Ji, Y., Saratchandran, H., Gordon, C., Zhang, Z., & Lucey, S. (2024). Sine Activated Low-Rank Matrices for Parameter Efficient Learning.. CoRR, abs/2403.19243. 2024 Ch'ng, S. -F., Saratchandran, H., & Lucey, S. (2024). Preconditioners for the Stochastic Training of Implicit Neural Representations.. CoRR, abs/2402.08784. 2024 Saratchandran, H., Ramasinghe, S., Shevchenko, V., Long, A., & Lucey, S. (2024). A Sampling Theory Perspective on Activations for Implicit Neural Representations. Proceedings of Machine Learning Research, 235, 43422-43444. 2024 Saratchandran, H., Ch'ng, S. -F., & Lucey, S. (2024). Architectural Strategies for the optimization of Physics-Informed Neural Networks.. CoRR, abs/2402.02711. 2024 Saratchandran, H., Ch'ng, S. -F., & Lucey, S. (2024). Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks.. CoRR, abs/2402.04783. 2023 Yin, M., Du, X., Liu, W., Yu, L., & Xing, Y. (2023). Multiscale Fusion Algorithm for Underwater Image Enhancement Based on Color Preservation. IEEE SENSORS JOURNAL, 23(7), 7728-7740.
2023 Yang, F., Sun, Y., Du, X., Chu, Z., Zhong, X., & Chen, X. (2023). Plant-specific histone deacetylases associate with ARGONAUTE4 to promote heterochromatin stabilization and plant heat tolerance. NEW PHYTOLOGIST, 238(1), 252-269.
2023 Murdock, C., Cazenavette, G., & Lucey, S. (2023). Reframing Neural Networks: Deep Structure in Overcomplete Representations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1), 964-979.
Scopus22023 Ramasinghe, S., Saratchandran, H., Shevchenko, V., & Lucey, S. (2023). On the effectiveness of neural priors in modeling dynamical systems.. CoRR, abs/2303.05728. 2023 Wang, C., MacDonald, L. E., Jeni, L. A., & Lucey, S. (2023). Flow Supervision for Deformable NeRF. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2023-June, 21128-21137.
Scopus162023 MacDonald, L. E., Valmadre, J., & Lucey, S. (2023). On progressive sharpening, flat minima and generalisation. 2023 Zheng, J., Li, X., Ramasinghe, S., & Lucey, S. (2023). Robust Point Cloud Processing through Positional Embedding. 2022 Ramasinghe, S., MacDonald, L. E., Farazi, M. R., Saratchandran, H., & Lucey, S. (2022). How You Start Matters for Generalization.. CoRR, abs/2206.08558. 2021 Li, L., Wang, J., Wu, C., & Ghahreman, A. (2021). An environmentally friendly method for efficient atmospheric oxidation of pyrrhotite in arsenopyrite/pyrite calcine. Chemical Engineering Journal Advances, 7, 9 pages.
Scopus12021 Kong, C., & Lucey, S. (2021). Deep Non-Rigid Structure from Motion with Missing Data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(12), 4365-4377.
Scopus82019 Sarode, V., Li, X., Goforth, H., Aoki, Y., Srivatsan, R. A., Lucey, S., & Choset, H. (2019). PCRNet: Point Cloud Registration Network using PointNet Encoding. 2019 Sarode, V., Li, X., Goforth, H., Aoki, Y., Dhagat, A., Srivatsan, R. A., . . . Choset, H. (2019). One Framework to Register Them All: PointNet Encoding for Point Cloud
Alignment.2017 Alismail, H., Browning, B., & Lucey, S. (2017). Photometric bundle adjustment for vision-based SLAM. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10114 LNCS, 324-341.
Scopus362017 Alismail, H., Browning, B., & Lucey, S. (2017). Enhancing direct camera tracking with dense feature descriptors. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10114 LNCS, 535-551.
Scopus22017 Alismail, H., Kaess, M., Browning, B., & Lucey, S. (2017). Direct Visual Odometry in Low Light Using Binary Descriptors. IEEE Robotics and Automation Letters, 2(2), 444-451.
Scopus592016 Shen, Y., Hu, W., Yang, M., Liu, J., Wei, B., Lucey, S., & Chou, C. T. (2016). Real-time and robust compressive background subtraction for embedded camera networks. IEEE Transactions on Mobile Computing, 15(2), 406-418.
Scopus39 WoS282015 Zhu, Y., & Lucey, S. (2015). Convolutional sparse coding for trajectory reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(3), 529-540.
Scopus92 WoS68 Europe PMC52013 Lucey, S., & Ashraf, A. B. (2013). Nearest neighbor classifier generalization through spatially constrained filters. Pattern Recognition, 46(1), 325-331.
Scopus5 WoS52013 Bennetts, R. J., Kim, J., Burke, D., Brooks, K. R., Lucey, S., Saragih, J., & Robbins, R. A. (2013). The movement advantage in famous and unfamiliar faces: A comparison of point-light displays and shape-normalised avatar stimuli. Perception, 42(9), 950-970.
Scopus10 WoS8 Europe PMC22013 Lucey, S., Navarathna, R., Ashraf, A. B., & Sridharan, S. (2013). Fourier Lucas-Kanade algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6), 1383-1396.
Scopus59 WoS45 Europe PMC62012 Dhall, A., Goecke, R., Lucey, S., & Gedeon, T. (2012). Collecting large, richly annotated facial-expression databases from movies. IEEE Multimedia, 19(3), 34-41.
Scopus510 WoS3272012 Chew, S. W., Lucey, P., Lucey, S., Saragih, J., Cohn, J. F., Matthews, I., & Sridharan, S. (2012). In the pursuit of effective affective computing: The relationship between features and registration. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(4), 1006-1016.
Scopus552011 Saragih, J. M., Lucey, S., & Cohn, J. F. (2011). Deformable model fitting by regularized landmark mean-shift. International Journal of Computer Vision, 91(2), 200-215.
Scopus708 WoS5442011 Asthana, A., Lucey, S., & Goecke, R. (2011). Regression based automatic face annotation for deformable model building. Pattern Recognition, 44(10-11), 2598-2613.
Scopus16 WoS112011 Lucey, P., Cohn, J. F., Matthews, I., Lucey, S., Sridharan, S., Howlett, J., & Prkachin, K. M. (2011). Automatically detecting pain in video through facial action units. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41(3), 664-674.
Scopus222 WoS160 Europe PMC402010 Ashraf, A. B., Lucey, S., & Chen, T. (2010). Reinterpreting the application of gabor filters as a manipulation of the margin in linear support vector machines. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(7), 1335-1341.
Scopus36 WoS18 Europe PMC32010 Lucey, S., Wang, Y., Saragih, J., & Cohn, J. F. (2010). Non-rigid face tracking with enforced convexity and local appearance consistency constraint. Image and Vision Computing, 28(5), 781-789.
Scopus17 WoS122009 Lucey, S., & Chen, T. (2009). Patches in Vision. Eurasip Journal on Image and Video Processing, 2009, 2 pages.
2009 Ashraf, A. B., Lucey, S., Cohn, J. F., Chen, T., Ambadar, Z., Prkachin, K. M., & Solomon, P. E. (2009). The painful face - Pain expression recognition using active appearance models. Image and Vision Computing, 27(12), 1788-1796.
Scopus281 WoS217 Europe PMC512009 Lucey, S., Wang, Y., Cox, M., Sridharan, S., & Cohn, J. F. (2009). Efficient constrained local model fitting for non-rigid face alignment. Image and Vision Computing, 27(12), 1804-1813.
Scopus33 WoS24 Europe PMC42008 Lucey, P., Howlett, J., Cohn, J., Lucey, S., Sridharan, S., & Ambadar, Z. (2008). Improving Pain Recognition Through Better Utilisation of Temporal Information. International Conference on Auditory-Visual Speech Processing 2008, AVSP 2008, 2008, 167-172.
Scopus242008 Lucey, S., & Chen, T. (2008). A viewpoint invariant, sparsely registered, patch based, face verifier. International Journal of Computer Vision, 80(1), 58-71.
Scopus17 WoS122007 Lucey, S., & Chen, T. (2007). Integrating monolithic and free-parts representations for improved face verification in the presence of pose mismatch. Pattern Recognition Letters, 28(8), 895-903.
2005 Lucey, S., Chen, T., Sridharan, S., & Chandran, V. (2005). Integration strategies for audio-visual speech processing: Applied to text-dependent speaker recognition. IEEE Transactions on Multimedia, 7(3), 495-506.
Scopus34 WoS202003 Lucey, S., Sridharan, S., & Chandran, V. (2003). Improved facial-feature detection for AVSP via unsupervised clustering and discriminant analysis. Eurasip Journal on Applied Signal Processing, 2003(3), 264-275.
Scopus11 WoS92003 Lucey, S. (2003). An evaluation of visual speech features for the tasks of speech and speaker recognition. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2688, 260-267.
Scopus152003 Lucey, S., & Chen, T. (2003). Improved audio-visual speaker recognition via the use of a hybrid combination strategy. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2688, 929-936.
2002 Lucey, S., Sridharan, S., & Chandran, V. (2002). Adaptive mouth segmentation using chromatic features. Pattern Recognition Letters, 23(11), 1293-1302.
Scopus20 WoS122000 Lucey, S. (2000). Initialised eigenlip estimator for fast lip tracking using linear regression. Proceedings - International Conference on Pattern Recognition, 15(3), 178-181.
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Book Chapters
Year Citation 2015 Ham, C., Lucey, S., & Singh, S. (2015). Absolute scale estimation of 3d monocular vision on smart devices. In Mobile Cloud Visual Media Computing: From Interaction to Service (pp. 329-353). Springer International Publishing.
DOI Scopus32015 Bristow, H., & Lucey, S. (2015). In defense of gradient-based alignment on densely sampled sparse features. In Dense Image Correspondences for Computer Vision (pp. 135-152). Springer International Publishing.
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Conference Papers
Year Citation 2025 Garg, R., Chng, S. F., & Lucey, S. (2025). Direct Alignment for Robust NeRF Learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 15480 LNCS (pp. 88-104). Hanoi: Springer Nature Singapore.
DOI2024 Dabhi, M., Jeni, L. A., & Lucey, S. (2024). 3D-LFM: Lifting Foundation Model. In 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (pp. 10466-10475). WA, Seattle: IEEE COMPUTER SOC.
DOI2024 Saratchandran, H., Wang, T. X., & Lucey, S. (2024). Weight Conditioning for Smooth Optimization of Neural Networks.. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, & G. Varol (Eds.), ECCV (85) Vol. 15143 (pp. 310-325). Springer. 2024 Vidanapathirana, K., Chng, S. F., Li, X., & Lucey, S. (2024). Multi-Body Neural Scene Flow. In Proceedings - 2024 International Conference on 3D Vision, 3DV 2024 (pp. 126-136). Online: IEEE.
DOI Scopus12024 Zheng, J., Li, X., Ramasinghe, S., & Lucey, S. (2024). Robust Point Cloud Processing Through Positional Embedding. In Proceedings - 2024 International Conference on 3D Vision, 3DV 2024 (pp. 1403-1412). Online: IEEE.
DOI2024 Saratchandran, H., Ramasinghe, S., Shevchenko, V., Long, A., & Lucey, S. (2024). A sampling theory perspective on activations for implicit neural representations.. In ICML (pp. 23 pages). Vienna, Austria: OpenReview.net. 2024 Seidenschwarz, J., Ošep, A., Ferroni, F., Lucey, S., & Leal-Taixé, L. (2024). SeMoLi: What Moves Together Belongs Together. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 14685-14694). Seattle, WA, USA: IEEE.
DOI2024 Li, X., Zheng, J., Ferroni, F., Pontes, J. K., & Lucey, S. (2024). Fast Neural Scene Flow. In Proceedings of the IEEE International Conference on Computer Vision (pp. 9844-9856). Online: IEEE.
DOI Scopus62024 Chang, M. F., Sharma, A., Kaess, M., & Lucey, S. (2024). Neural Radiance Fields with LiDAR Maps. In Proceedings of the IEEE International Conference on Computer Vision (pp. 17868-17877). Onine: IEEE.
DOI Scopus52024 Saratchandran, H., Ramasinghe, S., & Lucey, S. (2024). From Activation to Initialization: Scaling Insights for Optimizing Neural Fields.. In CVPR (pp. 413-422). Seattle, WA, USA: IEEE. 2024 Chodosh, N., Ramanan, D., & Lucey, S. (2024). Re-Evaluating LiDAR Scene Flow. In Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 (pp. 5993-6003). Online: IEEE.
DOI Scopus22024 Saratchandran, H., Chng, S. -F., Ramasinghe, S., MacDonald, L. E., & Lucey, S. (2024). Curvature-Aware Training for Coordinate Networks. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023) (pp. 13282-13292). online: IEEE.
DOI Scopus12023 Ramasinghe, S., MacDonald, L., Farazi, M., Saratchandran, H., & Lucey, S. (2023). How Much does Initialization Affect Generalization?. In ICML'23: Proceedings of the 40th International Conference on Machine Learning Vol. 202 (pp. 28637-28655). Honolulu, Hawaii, USA: Association for Computing Machinery. ACM.
Scopus22023 Gordon, C., Chng, S. F., MacDonald, L., & Lucey, S. (2023). On Quantizing Implicit Neural Representations. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV, 2023) (pp. 341-350). Online: IEEE.
DOI Scopus102023 Dabhi, M., Wang, C., Clifford, T., Jeni, L. A., Fasel, I., & Lucey, S. (2023). MBW: Multi-view Bootstrapping in the Wild. In Advances in Neural Information Processing Systems Vol. 35 (pp. 13 pages). USA: Neural information processing systems foundation. 2023 Ramasinghe, S., Macdonald, L., & Lucey, S. (2023). On the Frequency-Bias of Coordinate-MLPs. In Advances in Neural Information Processing Systems Vol. 35 (pp. 14 pages). USA: Neural information processing systems foundation.
Scopus52023 Ramasinghe, S., & Lucey, S. (2023). A Learnable Radial Basis Positional Embedding for Coordinate-MLPs. In B. Williams, Y. Chen, & J. Neville (Eds.), Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023 Vol. 37 (pp. 2137-2145). Washington, DC, USA: PKP Publishing Services Network.
DOI Scopus32023 MacDonald, L. E., Valmadre, J., Saratchandran, H., & Lucey, S. (2023). On skip connections and normalisation layers in deep optimisation.. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), NeurIPS Vol. 36 (pp. 20 pages). Online: Neural information processing systems foundation. 2022 MacDonald, L., Ramasinghe, S., & Lucey, S. (2022). Enabling Equivariance for Arbitrary Lie Groups. In Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New Orleans: IEEE. 2022 Ch'ng, S. F., Ramasinghe, S., Sherrah, J., & Lucey, S. (2022). GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation. In Proceedings of the 17th European Conference on Computer Vision (ECCV 2022). Tel Aviv, Israel. 2022 Dabhi, M., Wang, C., Saluja, K., Jeni, L. A., Fasel, I., & Lucey, S. (2022). High Fidelity 3D Reconstructions with Limited Physical Views. In Proceedings - 2021 International Conference on 3D Vision, 3DV 2021 (pp. 1301-1311). online: IEEE.
DOI Scopus3 WoS12022 Zheng, J., Ramasinghe, S., Li, X., & Lucey, S. (2022). Trading Positional Complexity vs Deepness in Coordinate Networks. In S. Avidan, G. Brostow, M. Cisse, G. M. Farinella, & T. Hassner (Eds.), Proceedings Computer Vision - ECCV Vol. 13687 LNCS (pp. 144-160). Tel Aviv, Israel: Springer Nature Switzerland.
DOI Scopus82022 Wang, C., Li, X., Pontes, J. K., & Lucey, S. (2022). Neural Prior for Trajectory Estimation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 6522-6532). Online: IEEE.
DOI Scopus132022 Chang, M. F., Zhao, Y., Shah, R., Engel, J. J., Kaess, M., & Lucey, S. (2022). Long-term Visual Map Sparsification with Heterogeneous GNN. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 2396-2405). Online: IEEE.
DOI Scopus42022 Chng, S. F., Ramasinghe, S., Sherrah, J., & Lucey, S. (2022). Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction and Pose Estimation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13693 LNCS (pp. 264-280). Online: Springer.
DOI Scopus36 WoS22022 Ramasinghe, S., & Lucey, S. (2022). Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13693 LNCS (pp. 142-158). Online: Springer.
DOI Scopus282022 Teney, D., Abbasnejad, E., Lucey, S., & Hengel, A. V. D. (2022). Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022) Vol. 2022-June (pp. 16740-16751). New Orleans, Louisiana: IEEE.
DOI Scopus40 WoS52022 MacDonald, L. E., Ramasinghe, S., & Lucey, S. (2022). Enabling Equivariance for Arbitrary Lie Groups. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2022-June (pp. 8173-8182). New Orleans, LA, USA: IEEE.
DOI Scopus9 WoS22021 Li, X., Pontes, J. K., & Lucey, S. (2021). Neural Scene Flow Prior. In Advances in Neural Information Processing Systems Vol. 34 (pp. 7838-7851). San Diego, CA, USA: Neural Information Processing Systems Foundation.
Scopus43 WoS22021 Wang, C., & Lucey, S. (2021). PAUL: Procrustean Autoencoder for Unsupervised Lifting. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 434-443). online: IEEE.
DOI Scopus13 WoS72021 Li, X., Pontes, J. K., & Lucey, S. (2021). PointNetlk revisited. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 12758-12767). Nashville, TN, USA: IEEE COMPUTER SOC.
DOI Scopus51 WoS72021 Cazenavette, G., Murdock, C., & Lucey, S. (2021). Architectural Adversarial Robustness: The Case for Deep Pursuit. In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 7146-7154). Nashville, TN, USA: IEEE.
DOI Scopus13 WoS72021 Lin, C. H., Ma, W. C., Torralba, A., & Lucey, S. (2021). BARF: Bundle-Adjusting Neural Radiance Fields. In Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 5721-5731). online: IEEE.
DOI Scopus368 WoS262021 Chang, M. F., Dong, W., Mangelson, J., Kaess, M., & Lucey, S. (2021). Map Compressibility Assessment for LiDAR Registration. In IEEE International Conference on Intelligent Robots and Systems (pp. 5560-5567). online: IEEE.
DOI Scopus4 WoS22021 Chang, M. F., Mangelson, J., Kaess, M., & Lucey, S. (2021). HyperMap: Compressed 3D map For Monocular Camera Registration. In Proceedings - IEEE International Conference on Robotics and Automation Vol. 2021-May (pp. 11140-11146). online: IEEE.
DOI Scopus8 WoS22021 Teney, D., Abbasnejad, E., Lucey, S., & Hengel, A. V. D. (2021). Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization.. In CoRR Vol. abs/2105.05612. 2020 Lin, C. H., Wang, C., & Lucey, S. (2020). SDF-SRN: Learning signed distance 3D object reconstruction from static images. In Advances in Neural Information Processing Systems, NeurIPS 2020 Vol. 2020-December (pp. 1-12). online: NIPS.
Scopus512020 Chodosh, N., & Lucey, S. (2020). When to use convolutional neural networks for inverse problems. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 8223-8232). online: IEEE.
DOI Scopus72020 Murdock, C., & Lucey, S. (2020). Dataless model selection with the deep frame potential. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 11254-11262). online: IEEE.
DOI Scopus32020 Sarode, V., Dhagat, A., Srivatsan, R. A., Zevallos, N., Lucey, S., & Choset, H. (2020). MaskNet: A Fully-Convolutional Network to Estimate Inlier Points. In Proceedings - 2020 International Conference on 3D Vision, 3DV 2020 (pp. 1029-1038). online: IEEE.
DOI Scopus282020 Pontes, J. K., Hays, J., & Lucey, S. (2020). Scene Flow from Point Clouds with or without Learning. In Proceedings - 2020 International Conference on 3D Vision, 3DV 2020 (pp. 261-270). online: IEEE.
DOI Scopus36 WoS132020 Wang, C., Lin, C. H., & Lucey, S. (2020). Deep NRSfM++: Towards Unsupervised 2D-3D Lifting in the Wild. In Proceedings - 2020 International Conference on 3D Vision, 3DV 2020 (pp. 12-22). online: IEEE.
DOI Scopus102020 Agrawal, S., Pahuja, A., & Lucey, S. (2020). High accuracy face geometry capture using a smartphone video. In Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020 (pp. 81-90). online: IEEE.
DOI Scopus42019 Pahuja, A., & Lucey, S. (2019). Lossy GIF compression using deep intrinsic parameterization. In Proceedings - 2019 International Conference on Computer Vision Workshop, ICCVW 2019 (pp. 4581-4583). online: IEEE.
DOI2019 Kong, C., & Lucey, S. (2019). Deep non-rigid structure from motion. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 1558-1567). online: IEEE.
DOI Scopus562019 Wang, C., Kong, C., & Lucey, S. (2019). Distill knowledge from NRSfM for weakly supervised 3D pose learning. In Proceedings of the IEEE International Conference on Computer Vision Vol. 2019-October (pp. 743-752). online: IEEE.
DOI Scopus422019 Chang, M. F., Lambert, J., Sangkloy, P., Singh, J., Bak, S., Hartnett, A., . . . Hays, J. (2019). Argoverse: 3D tracking and forecasting with rich maps. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) Vol. 2019-June (pp. 8740-8749). online: IEEE.
DOI Scopus9202019 Lin, C. H., Wang, O., Russell, B. C., Shechtman, E., Kim, V. G., Fisher, M., & Lucey, S. (2019). Photometric mesh optimization for video-aligned 3D object reconstruction. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) Vol. 2019-June (pp. 969-978). online: IEEE.
DOI Scopus522019 Aoki, Y., Goforth, H., Srivatsan, R. A., & Lucey, S. (2019). Pointnetlk: Robust & efficient point cloud registration using pointnet. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2019-June (pp. 7156-7165). online: IEEE.
DOI Scopus7112019 Goforth, H., & Lucey, S. (2019). GPS-denied UAV localization using pre-existing satellite imagery. In Proceedings - IEEE International Conference on Robotics and Automation (ICRA) Vol. 2019-May (pp. 2974-2980). online: IEEE.
DOI Scopus942019 Chodosh, N., Wang, C., & Lucey, S. (2019). Deep Convolutional Compressed Sensing for LiDAR Depth Completion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11361 LNCS (pp. 499-513). Switzerland: Springer Nature.
DOI Scopus732019 Wang, C., Lucey, S., Perazzi, F., & Wang, O. (2019). Web Stereo Video Supervision for Depth Prediction from Dynamic Scenes. In Proceedings - 2019 International Conference on 3D Vision, 3DV 2019 (pp. 348-357). online: IEEE.
DOI Scopus742019 Pontes, J. K., Kong, C., Sridharan, S., Lucey, S., Eriksson, A., & Fookes, C. (2019). Image2Mesh: A Learning Framework for Single Image 3D Reconstruction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11361 LNCS (pp. 365-381). Switzerland: Springer.
DOI Scopus672018 Kaesemodel Pontes, J., Kong, C., Eriksson, A., Fookes, C., Sridharan, S., & Lucey, S. (2018). Compact Model Representation for 3D Reconstruction. In Proceedings - 2017 International Conference on 3D Vision, 3DV 2017 (pp. 88-96). online: IEEE.
DOI Scopus92018 Ham, C., Chang, M. F., Lucey, S., & Singh, S. (2018). Monocular depth from small motion video accelerated. In Proceedings - 2017 International Conference on 3D Vision, 3DV 2017 (pp. 575-583). online: IEEE.
DOI Scopus6 WoS52018 Lin, C., Kong, C., & Lucey, S. (2018). Learning efficient point cloud generation for dense 3D object reconstruction. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 7114-7121). online: AAAI.
Scopus2962018 Wang, C., Buenaposada, J. M., Zhu, R., & Lucey, S. (2018). Learning Depth from Monocular Videos Using Direct Methods. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 2022-2030). online: IEEE.
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DOI Scopus7 -
Working Paper
Year Citation 2022 MacDonald, L. E., Saratchandran, H., Valmadre, J., & Lucey, S. (2022). A global analysis of global optimisation.. -
Internet Publications
Year Citation 2014 Valmadre, J., Sridharan, S., & Lucey, S. (2014). Learning detectors quickly using structured covariance matrices. -
Preprint
Year Citation 2025 Arunan, V., Nazar, S., Pramuditha, H., Viruthshaan, V., Ramasinghe, S., Lucey, S., & Rodrigo, R. (2025). DARB-Splatting: Generalizing Splatting with Decaying Anisotropic Radial
Basis Functions.2024 Saratchandran, H., Zheng, J., Ji, Y., Zhang, W., & Lucey, S. (2024). Rethinking Softmax: Self-Attention with Polynomial Activations. 2024 Fusco, C., Dabhi, M., Ch'ng, S. -F., & Lucey, S. (2024). Object Agnostic 3D Lifting in Space and Time. 2024 Chng, S. -F., Garg, R., Saratchandran, H., & Lucey, S. (2024). Invertible Neural Warp for NeRF. 2024 Saratchandran, H., Wang, T. X., & Lucey, S. (2024). Weight Conditioning for Smooth Optimization of Neural Networks. 2024 Zheng, J., Li, X., & Lucey, S. (2024). Structured Initialization for Attention in Vision Transformers. 2024 Li, X., & Lucey, S. (2024). Fast Kernel Scene Flow. 2024 Ji, Y., Saratchandran, H., Gordon, C., Zhang, Z., & Lucey, S. (2024). Efficient Learning With Sine-Activated Low-rank Matrices. 2024 Gordon, C., MacDonald, L. E., Saratchandran, H., & Lucey, S. (2024). D'OH: Decoder-Only Random Hypernetworks for Implicit Neural
Representations.2024 Chng, S. -F., Saratchandran, H., & Lucey, S. (2024). Preconditioners for the Stochastic Training of Implicit Neural
Representations.2024 Saratchandran, H., Ramasinghe, S., Shevchenko, V., Long, A., & Lucey, S. (2024). A Sampling Theory Perspective on Activations for Implicit Neural
Representations.2024 Zheng, J., Li, X., & Lucey, S. (2024). Convolutional Initialization for Data-Efficient Vision Transformers. 2024 Saratchandran, H., Chng, S. -F., & Lucey, S. (2024). Architectural Strategies for the optimization of Physics-Informed Neural
Networks.2024 Saratchandran, H., Chng, S. -F., & Lucey, S. (2024). Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate
Networks.2023 Li, X., Zheng, J., Ferroni, F., Pontes, J. K., & Lucey, S. (2023). Fast Neural Scene Flow. 2023 Saratchandran, H., Ch'ng, S. -F., Ramasinghe, S., MacDonald, L. E., & Lucey, S. (2023). Curvature-Aware Training for Coordinate Networks..
Professor Lucey has had numerous sources of funding from industry and the ARC. Please send him your CV if you are interested in pursuing a PhD or Post-Doc.
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2025 Principal Supervisor 3D applications of Artificial Intelligence Master of Philosophy Master Full Time Mr Irhas Muhammad Gill 2025 Co-Supervisor Transformers for Generative Multimodal AI Master of Philosophy Master Full Time Mr Zachary Liptak Shinnick 2024 Co-Supervisor Physical adversarial attacks against machine learning models for satellite imagery Doctor of Philosophy Doctorate Full Time Mr Harrison Taylor Bagley 2023 Principal Supervisor Understanding Sparse Geometry of 3D Objects in the Wild Master of Philosophy Master Full Time Mr Christopher Joseph Fusco 2023 Principal Supervisor Secrets of Implicit Neural Representation Doctor of Philosophy Doctorate Full Time Mr Yiping Ji 2021 Principal Supervisor Understanding Generalization and Memorization of Deep Neural Network from Distance and Rank Doctor of Philosophy Doctorate Full Time Mr Jianqiao Zheng 2021 Principal Supervisor Compressed Representation of Signals using Quantized Implicit Neural Representations Doctor of Philosophy Doctorate Full Time Mr Cameron Gordon 2021 Principal Supervisor Unsupervised Deep Geometry Doctor of Philosophy Doctorate Full Time Ms Xueqian Li
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