Thalaiyasingam Ajanthan

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 51

Top Topics

Weakly Supervised

Message Passing

Top Venues

Publications

Yixin Liu, Thalaiyasingam Ajanthan, Hisham Husain, Vu Nguyen
Self-Supervision Improves Diffusion Models for Tabular Data Imputation. CoRR (2024)
Yao Lu, Stephen Gould, Thalaiyasingam Ajanthan
Bidirectionally self-normalizing neural networks. Neural Networks 167 (2023)
Thalaiyasingam Ajanthan, Matt Ma, Anton van den Hengel, Stephen Gould
Adaptive Cross Batch Normalization for Metric Learning. CoRR (2023)
Peixia Li, Pulak Purkait, Thalaiyasingam Ajanthan, Majid Abdolshah, Ravi Garg, Hisham Husain, Chenchen Xu, Stephen Gould, Wanli Ouyang, Anton van den Hengel
Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups. ICCV (2023)
Luis Guerra, Thalaiyasingam Ajanthan, Gil Avraham, Yan Zou, Tom Drummond
Training 1-Bit Networks on a Sphere: A Geometric Approach. ICANN (3) (2022)
Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley
Few-shot Weakly-Supervised Object Detection via Directional Statistics. WACV (2022)
Kartik Gupta, Thalaiyasingam Ajanthan, Anton van den Hengel, Stephen Gould
Understanding and Improving the Role of Projection Head in Self-Supervised Learning. CoRR (2022)
Alexander Long, Wei Yin, Thalaiyasingam Ajanthan, Vu Nguyen, Pulak Purkait, Ravi Garg, Alan Blair, Chunhua Shen, Anton van den Hengel
Retrieval Augmented Classification for Long-Tail Visual Recognition. CVPR (2022)
Alexander Long, Wei Yin, Thalaiyasingam Ajanthan, Vu Nguyen, Pulak Purkait, Ravi Garg, Alan Blair, Chunhua Shen, Anton van den Hengel
Retrieval Augmented Classification for Long-Tail Visual Recognition. CoRR (2022)
Kartik Gupta, Thalaiyasingam Ajanthan
Improved Gradient-Based Adversarial Attacks for Quantized Networks. AAAI (2022)
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
Calibration of Neural Networks using Splines. ICLR (2021)
Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard I. Hartley
Few-shot Weakly-Supervised Object Detection via Directional Statistics. CoRR (2021)
Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania
Mirror Descent View for Neural Network Quantization. AISTATS (2021)
Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs. CoRR (2021)
Michele Sasdelli, Thalaiyasingam Ajanthan, Tat-Jun Chin, Gustavo Carneiro
A Chaos Theory Approach to Understand Neural Network Optimization. DICTA (2021)
Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi
Understanding the effects of data parallelism and sparsity on neural network training. ICLR (2021)
Kartik Gupta, Thalaiyasingam Ajanthan
Improved Gradient based Adversarial Attacks for Quantized Networks. CoRR (2020)
Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs. 3DV (2020)
Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs. CoRR (2020)
Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, Adnane Boukhayma, N. Siddharth, Philip H. S. Torr
DGPose: Deep Generative Models for Human Body Analysis. Int. J. Comput. Vis. 128 (5) (2020)
Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard I. Hartley, Byron Boots
Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization. ECCV (24) (2020)
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
Calibration of Neural Networks using Splines. CoRR (2020)
Zhiwei Xu, Thalaiyasingam Ajanthan, Richard I. Hartley
Fast and Differentiable Message Passing on Pairwise Markov Random Fields. ACCV (3) (2020)
Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard Hartley, Byron Boots
In Defense of Graph Inference Algorithms for Weakly Supervised Object Localization. CoRR (2020)
Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr
A Signal Propagation Perspective for Pruning Neural Networks at Initialization. ICLR (2020)
Zhiwei Xu, Thalaiyasingam Ajanthan, Richard I. Hartley
Deep Learning Superpixel Semantic Segmentation with Transparent Initialization and Sparse Encoder. CoRR (2020)
Amir Rahimi, Kartik Gupta, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
Post-hoc Calibration of Neural Networks. CoRR (2020)
Yao Lu, Stephen Gould, Thalaiyasingam Ajanthan
Bidirectional Self-Normalizing Neural Networks. CoRR (2020)
Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials. SIAM J. Imaging Sci. 12 (1) (2019)
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H. S. Torr, Marc'Aurelio Ranzato
Continual Learning with Tiny Episodic Memories. CoRR (2019)
Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr
Snip: single-Shot Network Pruning based on Connection sensitivity. ICLR (Poster) (2019)
Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley, Philip H. S. Torr
Proximal Mean-Field for Neural Network Quantization. ICCV (2019)
Thalaiyasingam Ajanthan, Richard Hartley, Mathieu Salzmann
Memory Efficient Max Flow for Multi-Label Submodular MRFs. IEEE Trans. Pattern Anal. Mach. Intell. 41 (4) (2019)
Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania
Mirror Descent View for Neural Network Quantization. CoRR (2019)
Alessio Tonioni, Oscar Rahnama, Thomas Joy, Luigi di Stefano, Thalaiyasingam Ajanthan, Philip H. S. Torr
Learning to Adapt for Stereo. CoRR (2019)
Alessio Tonioni, Oscar Rahnama, Thomas Joy, Luigi di Stefano, Thalaiyasingam Ajanthan, Philip H. S. Torr
Learning to Adapt for Stereo. CVPR (2019)
Zhiwei Xu, Thalaiyasingam Ajanthan, Richard Hartley
Fast and Differentiable Message Passing for Stereo Vision. CoRR (2019)
Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr
A Signal Propagation Perspective for Pruning Neural Networks at Initialization. CoRR (2019)
Rodrigo Andrade de Bem, Arnab Ghosh, Adnane Boukhayma, Thalaiyasingam Ajanthan, N. Siddharth, Philip H. S. Torr
A Conditional Deep Generative Model of People in Natural Images. WACV (2019)
Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr
SNIP: Single-shot Network Pruning based on Connection Sensitivity. CoRR (2018)
Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr
DGPose: Disentangled Semi-supervised Deep Generative Models for Human Body Analysis. CoRR (2018)
Richard I. Hartley, Thalaiyasingam Ajanthan
Generalized Range Moves. CoRR (2018)
Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr
A Semi-supervised Deep Generative Model for Human Body Analysis. ECCV Workshops (2) (2018)
Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan, Rudy Bunel, Mathieu Salzmann, Pushmeet Kohli, Philip H. S. Torr, M. Pawan Kumar
Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials. CoRR (2018)
Arslan Chaudhry, Puneet Kumar Dokania, Thalaiyasingam Ajanthan, Philip H. S. Torr
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence. CoRR (2018)
Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Richard I. Hartley, Philip H. S. Torr
Proximal Mean-field for Neural Network Quantization. CoRR (2018)
Arslan Chaudhry, Puneet Kumar Dokania, Thalaiyasingam Ajanthan, Philip H. S. Torr
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence. ECCV (11) (2018)
Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar
Efficient Linear Programming for Dense CRFs. CVPR (2017)
Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann
Memory Efficient Max Flow for Multi-label Submodular MRFs. CoRR (2017)
Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann
Memory Efficient Max Flow for Multi-label Submodular MRFs. CVPR (2016)
Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar
Efficient Linear Programming for Dense CRFs. CoRR (2016)
Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann, Hongdong Li
Iteratively reweighted graph cut for multi-label MRFs with non-convex priors. CVPR (2015)
Thalaiyasingam Ajanthan, Richard I. Hartley, Mathieu Salzmann, Hongdong Li
Iteratively Reweighted Graph Cut for Multi-label MRFs with Non-convex Priors. CoRR (2014)