Townim Chowdhury — accepted AI-conference papers

2025

Looking in the Mirror: A Faithful Counterfactual Explanation Method for Interpreting Deep Image Classification Models

Townim Chowdhury, Vu Minh Hieu Phan, Kewen Liao, Nanyu Dong, Minh-Son To, Anton van den Hengel +2

ICCV 2025poster

Counterfactual explanations (CFE) for deep image classifiers aim to reveal how minimal input changes lead to different model decisions, providing critical insights for model interpretation and improvement. However, existing CFE methods often rely on additional image encoders and generative models to…

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2022

Few-Shot Class-Incremental Learning for 3D Point Cloud Objects

Townim Chowdhury, Ali Cheraghian, Sameera Ramasinghe, Sahar Ahmadi, Morteza Saberi, Shafin Rahman

ECCV 2022poster

"Few-shot class-incremental learning (FSCIL) aims to incrementally fine-tune a model trained on base classes for a novel set of classes using a few examples without forgetting the previous training. Recent efforts of FSCIL addresses this problem primarily on 2D image data. However, due to the advanc…

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