Abstract

Computer vision aims at extracting useful information (e.g., objects, their boundaries, motion and 3D information, etc.) from images and videos. In this project, we aim at improving the state-of-the-art on various computer vision applications utilizing machine learning and optimization techniques.

Publications

Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups.
P. Li, P. Purkait, T. Ajanthan, M. Abdolshah, R. Garg, H. Husain, C. Xu, S. Gould, W. Ouyang, and A. van den Hengel.
International Conference on Computer Vision (ICCV), October 2023.
[pdf] [supp] [bib]

Adaptive Cross Batch Normalization for Metric Learning.
T. Ajanthan, M. Ma, A. van den Hengel, and S. Gould.
arxiv:2303.17127, March 2023.
[pdf] [arxiv] [bib]

Retrieval Augmented Classification for Long-tail Visual Recognition.
A. Long, W. Yin, T. Ajanthan, V. Nguyen, P. Purkait, R. Garg. A. Blair, C. Shen, and A. van den Hengel.
Computer Vision and Pattern Recognition (CVPR), June 2022.
[pdf] [arxiv] [bib]

Provable Defense Against Clustering Attacks on 3D Point Clouds.
D. D. Denipitiyage, T. Ajanthan, P. Kamalaruban, and A. Weller.
AAAI Workshop: Adversarial Machine Learning and Beyond, November 2022.
[pdf] [bib]

Refining Semantic Segmentation with Superpixel by Transparent Initialization and Sparse Encoder.
Zhiwei Xu, Thalaiyasingam Ajanthan, and Richard Hartley.
arxiv:2010.04363, November 2020.
[pdf] [arxiv] [bib]

Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization.
Amir Rahimi*, Amirreza Shaban*, Thalaiyasingam Ajanthan, Richard Hartley, and Byron Boots.
European Conference on Computer Vision (ECCV), August 2020.
[pdf] [arxiv] [bib]

Similarity Learning for One-Shot Video Object Segmentation.
Mohammad Najafi*, Viveka Kulharia*, Thalaiyasingam Ajanthan, and Philip H.S. Torr.
CVPR Workshop: DAVIS Challenge on Video Object Segmentation, June 2018.
[pdf] [bib]