22 citations · 62 across the 50 of their papers we have counts for
9 papers · 1 filter
Twin Trigger Generative Networks for Backdoor Attacks against Object Detection
Zhiying Li, Zhi Liu, Guanggang Geng +4
Object detectors, which are widely used in real-world applications, are vulnerable to backdoor attacks. This vulnerability arises because many users rely on datasets or pre-trained…
Principles of Visual Tokens for Efficient Video Understanding
Xinyue Hao, Gen Li, Shreyank N Gowda +4
Video understanding has made huge strides in recent years, relying largely on the power of transformers. As this architecture is notoriously expensive and video data is highly redu…
Continual Learning Improves Zero-Shot Action Recognition
Shreyank N Gowda, Davide Moltisanti, Laura Sevilla-Lara
Zero-shot action recognition requires a strong ability to generalize from pre-training and seen classes to novel unseen classes. Similarly, continual learning aims to develop model…
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos
Shreyank N Gowda, Boyan Gao, David A. Clifton
Utilizing large pre-trained models for specific tasks has yielded impressive results. However, fully fine-tuning these increasingly large models is becoming prohibitively resource-…
CC-SAM: SAM with Cross-feature Attention and Context for Ultrasound Image Segmentation
Shreyank N Gowda, David A. Clifton
The Segment Anything Model (SAM) has achieved remarkable successes in the realm of natural image segmentation, but its deployment in the medical imaging sphere has encountered chal…
Masks and Manuscripts: Advancing Medical Pre-training with End-to-End Masking and Narrative Structuring
Shreyank N Gowda, David A. Clifton
Contemporary medical contrastive learning faces challenges from inconsistent semantics and sample pair morphology, leading to dispersed and converging semantic shifts. The variabil…