Thalaiyasingam Ajanthan

According to our database, Thalaiyasingam Ajanthan authored at least 38 papers between 2015 and 2024.

Collaborative distances:

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

2024

Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame.

Evan Markou, Thalaiyasingam Ajanthan, Stephen Gould

CoRR, 2024

Accept the Modality Gap: An Exploration in the Hyperbolic Space.

Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Thalaiyasingam Ajanthan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Self-Supervision Improves Diffusion Models for Tabular Data Imputation.

Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain, Vu Nguyen

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Bidirectionally self-normalizing neural networks.

Yao Lu, Stephen Gould, Thalaiyasingam Ajanthan

Neural Networks, October, 2023

Adaptive Cross Batch Normalization for Metric Learning.

Thalaiyasingam Ajanthan, Matt Ma, Anton van den Hengel, Stephen Gould

CoRR, 2023

Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups.

Peixia Li, Pulak Purkait, Thalaiyasingam Ajanthan, Majid Abdolshah, Ravi Garg, Hisham Husain, Chenchen Xu, Stephen Gould, Wanli Ouyang, Anton van den Hengel

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

2022

Understanding and Improving the Role of Projection Head in Self-Supervised Learning.

Kartik Gupta, Thalaiyasingam Ajanthan, Anton van den Hengel, Stephen Gould

CoRR, 2022

Few-shot Weakly-Supervised Object Detection via Directional Statistics.

Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Training 1-Bit Networks on a Sphere: A Geometric Approach.

Luis Guerra, Thalaiyasingam Ajanthan, Gil Avraham, Yan Zou, Tom Drummond

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Retrieval Augmented Classification for Long-Tail Visual Recognition.

Alexander Long, Wei Yin, Thalaiyasingam Ajanthan, Vu Nguyen, Pulak Purkait, Ravi Garg, Alan Blair, Chunhua Shen, Anton van den Hengel

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

Improved Gradient-Based Adversarial Attacks for Quantized Networks.

Kartik Gupta, Thalaiyasingam Ajanthan

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Understanding the effects of data parallelism and sparsity on neural network training.

Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi

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

Calibration of Neural Networks using Splines.

Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley

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

A Chaos Theory Approach to Understand Neural Network Optimization.

Michele Sasdelli, Thalaiyasingam Ajanthan, Tat-Jun Chin, Gustavo Carneiro

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

Mirror Descent View for Neural Network Quantization.

Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

DGPose: Deep Generative Models for Human Body Analysis.

Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, Adnane Boukhayma, N. Siddharth, Philip H. S. Torr

Int. J. Comput. Vis., 2020

Deep Learning Superpixel Semantic Segmentation with Transparent Initialization and Sparse Encoder.

Zhiwei Xu, Thalaiyasingam Ajanthan, Richard I. Hartley

CoRR, 2020

Post-hoc Calibration of Neural Networks.

Amir Rahimi, Kartik Gupta, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley

CoRR, 2020

Bidirectional Self-Normalizing Neural Networks.

Yao Lu, Stephen Gould, Thalaiyasingam Ajanthan

CoRR, 2020

In Defense of Graph Inference Algorithms for Weakly Supervised Object Localization.

Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard Hartley, Byron Boots

CoRR, 2020

A Signal Propagation Perspective for Pruning Neural Networks at Initialization.

Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr

Proceedings of the 8th International Conference on Learning Representations, 2020

Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization.

Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard I. Hartley, Byron Boots

Proceedings of the Computer Vision - ECCV 2020, 2020

Fast and Differentiable Message Passing on Pairwise Markov Random Fields.

Zhiwei Xu, Thalaiyasingam Ajanthan, Richard I. Hartley

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs.

Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley

Proceedings of the 8th International Conference on 3D Vision, 2020

2019

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials.

Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar

SIAM J. Imaging Sci., 2019

Memory Efficient Max Flow for Multi-Label Submodular MRFs.

Thalaiyasingam Ajanthan, Richard Hartley, Mathieu Salzmann

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Fast and Differentiable Message Passing for Stereo Vision.

Zhiwei Xu, Thalaiyasingam Ajanthan, Richard Hartley

CoRR, 2019

Continual Learning with Tiny Episodic Memories.

Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H. S. Torr, Marc'Aurelio Ranzato

CoRR, 2019

A Conditional Deep Generative Model of People in Natural Images.

Rodrigo Andrade de Bem, Arnab Ghosh, Adnane Boukhayma, Thalaiyasingam Ajanthan, N. Siddharth, Philip H. S. Torr

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Snip: single-Shot Network Pruning based on Connection sensitivity.

Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr

Proceedings of the 7th International Conference on Learning Representations, 2019

Proximal Mean-Field for Neural Network Quantization.

Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley, Philip H. S. Torr

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Learning to Adapt for Stereo.

Alessio Tonioni, Oscar Rahnama, Thomas Joy, Luigi Di Stefano, Thalaiyasingam Ajanthan, Philip H. S. Torr

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Generalized Range Moves.

Richard I. Hartley, Thalaiyasingam Ajanthan

CoRR, 2018

DGPose: Disentangled Semi-supervised Deep Generative Models for Human Body Analysis.

Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr

CoRR, 2018

Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence.

Arslan Chaudhry, Puneet Kumar Dokania, Thalaiyasingam Ajanthan, Philip H. S. Torr

Proceedings of the Computer Vision - ECCV 2018, 2018

A Semi-supervised Deep Generative Model for Human Body Analysis.

Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017

Efficient Linear Programming for Dense CRFs.

Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2015

Iteratively reweighted graph cut for multi-label MRFs with non-convex priors.

Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann, Hongdong Li

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015