Jathushan Rajasegaran

Orcid: 0000-0003-1081-4254

According to our database1, Jathushan Rajasegaran authored at least 28 papers between 2017 and 2024.

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Bibliography

2024
Synergy and Synchrony in Couple Dances.
CoRR, 2024

FewShotNeRF: Meta-Learning-based Novel View Synthesis for Rapid Scene-Specific Adaptation.
CoRR, 2024

Humanoid Locomotion as Next Token Prediction.
CoRR, 2024

Synthesizing Moving People with 3D Control.
CoRR, 2024

EgoPet: Egomotion and Interaction Data from an Animal's Perspective.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Humans in 4D: Reconstructing and Tracking Humans with Transformers.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On the Benefits of 3D Pose and Tracking for Human Action Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
A Multi-Modal Neural Embeddings Approach for Detecting Mobile Counterfeit Apps: A Case Study on Google Play Store.
IEEE Trans. Mob. Comput., 2022

Incremental Object Detection via Meta-Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Fully Online Meta-Learning Without Task Boundaries.
CoRR, 2022

Tracking People by Predicting 3D Appearance, Location and Pose.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Power Control for Body Area Networks: Accurate Channel Prediction by Lightweight Deep Learning.
IEEE Internet Things J., 2021

Tracking People by Predicting 3D Appearance, Location & Pose.
CoRR, 2021

Tracking People with 3D Representations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-learning the Learning Trends Shared Across Tasks.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Self-supervised Knowledge Distillation for Few-shot Learning.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Incremental Object Detection via Meta-Learning.
CoRR, 2020

iTAML: An Incremental Task-Agnostic Meta-learning Approach.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Combined Static and Motion Features for Deep-Networks-Based Activity Recognition in Videos.
IEEE Trans. Circuits Syst. Video Technol., 2019

TimeCaps: Capturing Time Series Data with Capsule Networks.
CoRR, 2019

Random Path Selection for Incremental Learning.
CoRR, 2019

A Multi-modal Neural Embeddings Approach for Detecting Mobile Counterfeit Apps.
Proceedings of the World Wide Web Conference, 2019

TextCaps: Handwritten Character Recognition With Very Small Datasets.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Random Path Selection for Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DeepCaps: Going Deeper With Capsule Networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Performance Characterization of Deep Learning Models for Breathing-based Authentication on Resource-Constrained Devices.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018

A Neural Embeddings Approach for Detecting Mobile Counterfeit Apps.
CoRR, 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


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