Sameera Ramasinghe

According to our database, Sameera Ramasinghe authored at least 38 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

From Activation to Initialization: Scaling Insights for Optimizing Neural Fields.

Hemanth Saratchandran, Sameera Ramasinghe, Simon Lucey

CoRR, 2024

Backpropagation-free Network for 3D Test-time Adaptation.

Yanshuo Wang, Ali Cheraghian, Zeeshan Hayder, Jie Hong, Sameera Ramasinghe, Shafin Rahman, David Ahmedt-Aristizabal, Xuesong Li, Lars Petersson, Mehrtash Harandi

CoRR, 2024

ViewFusion: Towards Multi-View Consistency via Interpolated Denoising.

Xianghui Yang, Yan Zuo, Sameera Ramasinghe, Loris Bazzani, Gil Avraham, Anton van den Hengel

CoRR, 2024

A Sampling Theory Perspective on Activations for Implicit Neural Representations.

Hemanth Saratchandran, Sameera Ramasinghe, Violetta Shevchenko, Alexander Long, Simon Lucey

CoRR, 2024

BLiRF: Bandlimited Radiance Fields for Dynamic Scene Modeling.

Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Anton van den Hengel

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

LumiNet: The Bright Side of Perceptual Knowledge Distillation.

Md. Ismail Hossain, Mirza M. Lutfe Elahi, Sameera Ramasinghe, Ali Cheraghian, Fuad Rahman, Nabeel Mohammed, Shafin Rahman

CoRR, 2023

Robust Point Cloud Processing through Positional Embedding.

Jianqiao Zheng, Xueqian Li, Sameera Ramasinghe, Simon Lucey

CoRR, 2023

On the effectiveness of neural priors in modeling dynamical systems.

Sameera Ramasinghe, Hemanth Saratchandran, Violetta Shevchenko, Simon Lucey

CoRR, 2023

BaLi-RF: Bandlimited Radiance Fields for Dynamic Scene Modeling.

Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Anton van den Hengel

CoRR, 2023

How much does Initialization Affect Generalization?

Sameera Ramasinghe, Lachlan Ewen MacDonald, Moshiur R. Farazi, Hemanth Saratchandran, Simon Lucey

Proceedings of the International Conference on Machine Learning, 2023

Curvature-Aware Training for Coordinate Networks.

Hemanth Saratchandran, Shin-Fang Chng, Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Learnable Radial Basis Positional Embedding for Coordinate-MLPs.

Sameera Ramasinghe, Simon Lucey

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

How You Start Matters for Generalization.

Sameera Ramasinghe, Lachlan E. MacDonald, Moshiur R. Farazi, Hemanth Saratchandran, Simon Lucey

CoRR, 2022

GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation.

Shin-Fang Chng, Sameera Ramasinghe, Jamie Sherrah, Simon Lucey

CoRR, 2022

On Regularizing Coordinate-MLPs.

Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

CoRR, 2022

On the Frequency-bias of Coordinate-MLPs.

Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Trading Positional Complexity vs Deepness in Coordinate Networks.

Jianqiao Zheng, Sameera Ramasinghe, Xueqian Li, Simon Lucey

Proceedings of the Computer Vision - ECCV 2022, 2022

Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs.

Sameera Ramasinghe, Simon Lucey

Proceedings of the Computer Vision - ECCV 2022, 2022

Few-Shot Class-Incremental Learning for 3D Point Cloud Objects.

Townim F. Chowdhury, Ali Cheraghian, Sameera Ramasinghe, Sahar Ahmadi, Morteza Saberi, Shafin Rahman

Proceedings of the Computer Vision - ECCV 2022, 2022

Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction and Pose Estimation.

Shin-Fang Chng, Sameera Ramasinghe, Jamie Sherrah, Simon Lucey

Proceedings of the Computer Vision - ECCV 2022, 2022

Enabling Equivariance for Arbitrary Lie Groups.

Lachlan E. MacDonald, Sameera Ramasinghe, Simon Lucey

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Robust normalizing flows using Bernstein-type polynomials.

Sameera Ramasinghe, Kasun Fernando, Salman Khan, Nick Barnes

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Learning Positional Embeddings for Coordinate-MLPs.

Sameera Ramasinghe, Simon Lucey

CoRR, 2021

Rethinking Positional Encoding.

Jianqiao Zheng, Sameera Ramasinghe, Simon Lucey

CoRR, 2021

Rethinking conditional GAN training: An approach using geometrically structured latent manifolds.

Sameera Ramasinghe, Moshiur R. Farazi, Salman H. Khan, Nick Barnes, Stephen Gould

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Conditional Generative Modeling via Learning the Latent Space.

Sameera Ramasinghe, Kanchana Nisal Ranasinghe, Salman H. Khan, Nick Barnes, Stephen Gould

Proceedings of the 9th International Conference on Learning Representations, 2021

Synthesized Feature based Few-Shot Class-Incremental Learning on a Mixture of Subspaces.

Ali Cheraghian, Shafin Rahman, Sameera Ramasinghe, Pengfei Fang, Christian Simon, Lars Petersson, Mehrtash Harandi

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Representation Learning on Unit Ball with 3D Roto-translational Equivariance.

Sameera Ramasinghe, Salman H. Khan, Nick Barnes, Stephen Gould

Int. J. Comput. Vis., 2020

How to train your conditional GAN: An approach using geometrically structured latent manifolds.

Sameera Ramasinghe, Moshiur R. Farazi, Salman H. Khan, Nick Barnes, Stephen Gould

CoRR, 2020

Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes.

Sameera Ramasinghe, Salman H. Khan, Nick Barnes, Stephen Gould

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Spectral-GANs for High-Resolution 3D Point-cloud Generation.

Sameera Ramasinghe, Salman H. Khan, Nick Barnes, Stephen Gould

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learned and Hand-crafted Feature Fusion in Unit Ball for 3D Object Classification.

Sameera Ramasinghe, Salman H. Khan, Nick Barnes

Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020

2019

Combined Static and Motion Features for Deep-Networks-Based Activity Recognition in Videos.

Sameera Ramasinghe, Jathushan Rajasegaran, Vinoj Jayasundara, Kanchana Ranasinghe, Ranga Rodrigo, Ajith A. Pasqual

IEEE Trans. Circuits Syst. Video Technol., 2019

Volumetric Convolution: Automatic Representation Learning in Unit Ball.

Sameera Ramasinghe, Salman H. Khan, Nick Barnes

CoRR, 2019

2018

A Context-Aware Capsule Network for Multi-label Classification.

Sameera Ramasinghe, C. D. Athuraliya, Salman H. Khan

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017

Micro Actions and Deep Static Features for Activity Recognition.

Sameera Ramasinghe, Jathushan Rajasegaran, Vinoj Jayasundara, Kanchana Ranasinghe, Ranga Rodrigo, Ajith A. Pasqual

Proceedings of the 2017 International Conference on Digital Image Computing: Techniques and Applications, 2017

2016

Poster: Advanced Feature Based Deep Learning for Intelligent Human Activity Recognition: An Approach using Scene Context and Composition of Sub Events.

Sameera Ramasinghe

Proceedings of the 14th Annual International Conference on Mobile Systems, 2016

2015

Action recognition by single stream convolutional neural networks: An approach using combined motion and static information.

Sameera Ramasinghe, Ranga Rodrigo

Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition, 2015