Search Results for author:
Found 6 papers, 5 papers with code
Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation (WSSS) aims to bypass the need for laborious pixel-level annotation by using only image-level annotation.
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation
In this paper, we propose TransCAM, a Conformer-based solution to WSSS that explicitly leverages the attention weights from the transformer branch of the Conformer to refine the CAM generated from the CNN branch.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification
Contrastive learning has led to substantial improvements in the quality of learned embedding representations for tasks such as image classification.
EDDA: Explanation-driven Data Augmentation to Improve Explanation Faithfulness
Recent years have seen the introduction of a range of methods for post-hoc explainability of image classifier predictions.
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning
Online class-incremental continual learning (CL) studies the problem of learning new classes continually from an online non-stationary data stream, intending to adapt to new data while mitigating catastrophic forgetting.
Online Continual Learning in Image Classification: An Empirical Survey
To better understand the relative advantages of various approaches and the settings where they work best, this survey aims to (1) compare state-of-the-art methods such as MIR, iCARL, and GDumb and determine which works best at different experimental settings; (2) determine if the best class incremental methods are also competitive in domain incremental setting; (3) evaluate the performance of 7 simple but effective trick such as "review" trick and nearest class mean (NCM) classifier to assess their relative impact.
