Thalaiyasingam Ajanthan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
26
Venues
13
Active years
2015–2025
Best venue rank
A*
Where they publish
Papers
26 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICCV | Learning Visual Hierarchies in Hyperbolic Space for Image Retrieval. | Ziwei Wang, Sameera Ramasinghe, Chenchen Hu, Julien Monteil, Loris Bazzani, Thalaiyasingam Ajanthan |
| 2025 | ICML | Nesterov Method for Asynchronous Pipeline Parallel Optimization. | Thalaiyasingam Ajanthan, Sameera Ramasinghe, Yan Zuo, Gil Avraham, Alexander Long |
| 2025 | IJCNN | Scaling Prompt Instructed Zero Shot Composed Image Retrieval with Image-Only Data. | Yiqun Duan, Sameera Ramasinghe, Stephen Gould, Thalaiyasingam Ajanthan |
| 2024 | CIKM | Self-Supervision Improves Diffusion Models for Tabular Data Imputation. | Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain, Vu Nguyen |
| 2024 | CVPR | Accept the Modality Gap: An Exploration in the Hyperbolic Space. | Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Thalaiyasingam Ajanthan |
| 2023 | ICCV | 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 |
| 2022 | AAAI | Improved Gradient-Based Adversarial Attacks for Quantized Networks. | Kartik Gupta, Thalaiyasingam Ajanthan |
| 2022 | CVPR | 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 |
| 2022 | ICANN | Training 1-Bit Networks on a Sphere: A Geometric Approach. | Luis Guerra, Thalaiyasingam Ajanthan, Gil Avraham, Yan Zou, Tom Drummond |
| 2022 | WACV | Few-shot Weakly-Supervised Object Detection via Directional Statistics. | Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley |
| 2021 | AISTATS | Mirror Descent View for Neural Network Quantization. | Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania |
| 2021 | DICTA | A Chaos Theory Approach to Understand Neural Network Optimization. | Michele Sasdelli, Thalaiyasingam Ajanthan, Tat-Jun Chin, Gustavo Carneiro |
| 2021 | ICLR | Calibration of Neural Networks using Splines. | Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley |
| 2021 | ICLR | Understanding the effects of data parallelism and sparsity on neural network training. | Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi |
| 2020 | ACCV | Fast and Differentiable Message Passing on Pairwise Markov Random Fields. | Zhiwei Xu, Thalaiyasingam Ajanthan, Richard I. Hartley |
| 2020 | ECCV | Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization. | Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard I. Hartley, Byron Boots |
| 2020 | ICLR | A Signal Propagation Perspective for Pruning Neural Networks at Initialization. | Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr |
| 2019 | CVPR | Learning to Adapt for Stereo. | Alessio Tonioni, Oscar Rahnama, Thomas Joy, Luigi Di Stefano, Thalaiyasingam Ajanthan, Philip H. S. Torr |
| 2019 | ICCV | Proximal Mean-Field for Neural Network Quantization. | Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley, Philip H. S. Torr |
| 2019 | ICLR | Snip: single-Shot Network Pruning based on Connection sensitivity. | Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr |
| 2019 | WACV | 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 |
| 2018 | ECCV | 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 |
| 2018 | ECCV | Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence. | Arslan Chaudhry, Puneet Kumar Dokania, Thalaiyasingam Ajanthan, Philip H. S. Torr |
| 2017 | CVPR | Efficient Linear Programming for Dense CRFs. | Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar |
| 2016 | CVPR | Memory Efficient Max Flow for Multi-label Submodular MRFs. | Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann |
| 2015 | CVPR | Iteratively reweighted graph cut for multi-label MRFs with non-convex priors. | Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann, Hongdong Li |