Sameera Ramasinghe

Orcid: 0000-0002-3200-9291

According to our database1, Sameera Ramasinghe authored at least 42 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Neural Experts: Mixture of Experts for Implicit Neural Representations.
CoRR, 2024

A sampling theory perspective on activations for implicit neural representations.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Improving the Convergence of Dynamic NeRFs via Optimal Transport.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Canonical Shape Projection Is All You Need for 3D Few-Shot Class Incremental Learning.
Proceedings of the Computer Vision - ECCV 2024, 2024

ViewFusion: Towards Multi-View Consistency via Interpolated Denoising.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Backpropagation-free Network for 3D Test-time Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

From Activation to Initialization: Scaling Insights for Optimizing Neural Fields.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Accept the Modality Gap: An Exploration in the Hyperbolic Space.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

BLiRF: Bandlimited Radiance Fields for Dynamic Scene Modeling.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Robust Point Cloud Processing Through Positional Embedding.
Proceedings of the International Conference on 3D Vision, 2024

2023
LumiNet: The Bright Side of Perceptual Knowledge Distillation.
CoRR, 2023

On the effectiveness of neural priors in modeling dynamical systems.
CoRR, 2023

BaLi-RF: Bandlimited Radiance Fields for Dynamic Scene Modeling.
CoRR, 2023

How much does Initialization Affect Generalization?
Proceedings of the International Conference on Machine Learning, 2023

Curvature-Aware Training for Coordinate Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Learnable Radial Basis Positional Embedding for Coordinate-MLPs.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
How You Start Matters for Generalization.
CoRR, 2022

GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation.
CoRR, 2022

On Regularizing Coordinate-MLPs.
CoRR, 2022

On the Frequency-bias of Coordinate-MLPs.
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.
Proceedings of the Computer Vision - ECCV 2022, 2022

Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs.
Proceedings of the Computer Vision - ECCV 2022, 2022

Few-Shot Class-Incremental Learning for 3D Point Cloud Objects.
Proceedings of the Computer Vision - ECCV 2022, 2022

Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction and Pose Estimation.
Proceedings of the Computer Vision - ECCV 2022, 2022

Enabling Equivariance for Arbitrary Lie Groups.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Robust normalizing flows using Bernstein-type polynomials.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
Learning Positional Embeddings for Coordinate-MLPs.
CoRR, 2021

Rethinking Positional Encoding.
CoRR, 2021

Rethinking conditional GAN training: An approach using geometrically structured latent manifolds.
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.
Proceedings of the 9th International Conference on Learning Representations, 2021

Synthesized Feature based Few-Shot Class-Incremental Learning on a Mixture of Subspaces.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Representation Learning on Unit Ball with 3D Roto-translational Equivariance.
Int. J. Comput. Vis., 2020

How to train your conditional GAN: An approach using geometrically structured latent manifolds.
CoRR, 2020

Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Spectral-GANs for High-Resolution 3D Point-cloud Generation.
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.
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.
IEEE Trans. Circuits Syst. Video Technol., 2019

Volumetric Convolution: Automatic Representation Learning in Unit Ball.
CoRR, 2019

2018
A Context-Aware Capsule Network for Multi-label Classification.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017
Micro Actions and Deep Static Features for Activity Recognition.
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.
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.
Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition, 2015


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