| Synthesized feature based few-shot class-incremental learning on a mixture of subspaces A Cheraghian, S Rahman, S Ramasinghe, P Fang, C Simon, L Petersson, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 24 | 2021 |
| Spectral-GANs for high-resolution 3D point-cloud generation S Ramasinghe, S Khan, N Barnes, S Gould 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 22 | 2020 |
| Action recognition by single stream convolutional neural networks: An approach using combined motion and static information S Ramasinghe, R Rodrigo 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 101-105, 2015 | 17 | 2015 |
| Rethinking positional encoding J Zheng, S Ramasinghe, S Lucey arXiv preprint arXiv:2107.02561, 2021 | 16 | 2021 |
| Beyond periodicity: towards a unifying framework for activations in coordinate-MLPs S Ramasinghe, S Lucey Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 14 | 2022 |
| Recognition of badminton strokes using dense trajectories S Ramasinghe, KGM Chathuramali, R Rodrigo 7th International Conference on Information and Automation for …, 2014 | 13 | 2014 |
| Representation learning on unit ball with 3d roto-translational equivariance S Ramasinghe, S Khan, N Barnes, S Gould International Journal of Computer Vision 128 (6), 1612-1634, 2020 | 10 | 2020 |
| Combined static and motion features for deep-networks-based activity recognition in videos S Ramasinghe, J Rajasegaran, V Jayasundara, K Ranasinghe, ... IEEE Transactions on Circuits and Systems for Video Technology 29 (9), 2693-2707, 2017 | 10 | 2017 |
| A context-aware capsule network for multi-label classification S Ramasinghe, CD Athuraliya, SH Khan Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 9 | 2018 |
| Enabling equivariance for arbitrary Lie groups LE MacDonald, S Ramasinghe, S Lucey Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 6 | 2022 |
| Robust normalizing flows using Bernstein-type polynomials S Ramasinghe, K Fernando, S Khan, N Barnes arXiv preprint arXiv:2102.03509, 2021 | 6 | 2021 |
| Abnormal activity recognition using spatio-temporal features KGM Chathuramali, S Ramasinghe, R Rodrigo 7th International Conference on Information and Automation for …, 2014 | 6 | 2014 |
| GARF: gaussian activated radiance fields for high fidelity reconstruction and pose estimation SF Chng, S Ramasinghe, J Sherrah, S Lucey arXiv e-prints, arXiv: 2204.05735, 2022 | 5 | 2022 |
| Learning positional embeddings for coordinate-MLPs S Ramasinghe, S Lucey arXiv preprint arXiv:2112.11577, 2021 | 5 | 2021 |
| Rethinking conditional GAN training: An approach using geometrically structured latent manifolds S Ramasinghe, M Farazi, SH Khan, N Barnes, S Gould Advances in Neural Information Processing Systems 34, 19487-19499, 2021 | 5 | 2021 |
| Conditional Generative Modeling via Learning the Latent Space S Ramasinghe, K Ranasinghe, S Khan, N Barnes, S Gould International Conference on Learning Representations. 2020., 2020 | 5 | 2020 |
| Gaussian activated neural radiance fields for high fidelity reconstruction and pose estimation SF Chng, S Ramasinghe, J Sherrah, S Lucey Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 4 | 2022 |
| Blended convolution and synthesis for efficient discrimination of 3D shapes S Ramasinghe, S Khan, N Barnes, S Gould Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 4 | 2020 |
| Volumetric convolution: Automatic representation learning in unit ball S Ramasinghe, S Khan, N Barnes arXiv preprint arXiv:1901.00616, 2019 | 4 | 2019 |
| On regularizing coordinate-mlps S Ramasinghe, L MacDonald, S Lucey arXiv preprint arXiv:2202.00790, 2022 | 2 | 2022 |
Simon LuceyProfessor, University of AdelaideVerified email at adelaide.edu
