| Gaussian activated neural radiance fields for high fidelity reconstruction and pose estimation SF Chng, S Ramasinghe, J Sherrah, S Lucey European Conference on Computer Vision, 264-280, 2022 | 81 | 2022 |
| Beyond periodicity: Towards a unifying framework for activations in coordinate-mlps S Ramasinghe, S Lucey European Conference on Computer Vision, 142-158, 2022 | 75 | 2022 |
| 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 | 61 | 2021 |
| Rethinking positional encoding J Zheng, S Ramasinghe, S Lucey arXiv preprint arXiv:2107.02561, 2021 | 43 | 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 | 35 | 2020 |
| Enabling equivariance for arbitrary lie groups LE MacDonald, S Ramasinghe, S Lucey Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 23 | 2022 |
| 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 | 21 | 2015 |
| Recognition of badminton strokes using dense trajectories S Ramasinghe, KGM Chathuramali, R Rodrigo 7th International Conference on Information and Automation for …, 2014 | 19 | 2014 |
| 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 | 16 | 2018 |
| Trading positional complexity vs deepness in coordinate networks J Zheng, S Ramasinghe, X Li, S Lucey European Conference on Computer Vision, 144-160, 2022 | 15 | 2022 |
| 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 | 15 | 2017 |
| 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 | 11 | 2021 |
| On the frequency-bias of coordinate-mlps S Ramasinghe, LE MacDonald, S Lucey Advances in Neural Information Processing Systems 35, 796-809, 2022 | 10 | 2022 |
| Robust normalizing flows using Bernstein-type polynomials S Ramasinghe, K Fernando, S Khan, N Barnes arXiv preprint arXiv:2102.03509, 2021 | 10 | 2021 |
| 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 |
| Few-shot class-incremental learning for 3d point cloud objects T Chowdhury, A Cheraghian, S Ramasinghe, S Ahmadi, M Saberi, ... European Conference on Computer Vision, 204-220, 2022 | 9 | 2022 |
| Learning positional embeddings for coordinate-mlps S Ramasinghe, S Lucey arXiv preprint arXiv:2112.11577, 2021 | 8 | 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 | 8 | 2020 |
| Spectral-gans for high-resolution 3d point-cloud generation. In 2020 IEEE S Ramasinghe, S Khan, N Barnes, S Gould RSJ International Conference on Intelligent Robots and Systems (IROS), 8169-8176, 0 | 8 | |
| BLiRF: Bandlimited Radiance Fields for Dynamic Scene Modeling S Ramasinghe, V Shevchenko, G Avraham, A Van Den Hengel Proceedings of the AAAI Conference on Artificial Intelligence 38 (5), 4641-4649, 2024 | 6 | 2024 |
Simon LuceyProfessor, University of Adelaide在 adelaide.edu 的电子邮件经过验证
