4 papers
Suppress and Diversify: Refining Robust Pathways for Corruption Robustness
Jiangang Yang, Wenhui Shi, Xiaoran Xu +4
Model robustness against natural image corruptions is essential for safety-critical applications. While existing methods primarily focus on implicit representation learning, we pro…
Robustness Emerges Early in Training Dynamics, but Is Not Preserved
Jiangang Yang, Wenhui Shi, Lu Hu +2
Robustness to natural corruptions remains a fundamental challenge for deep neural networks. In this paper, we identify a robustness fading phenomenon where shallow layers spontaneo…
Boosting Single-domain Generalized Object Detection via Vision-Language Knowledge Interaction
Xiaoran Xu, Jiangang Yang, Wenyue Chong +4
Single-Domain Generalized Object Detection~(S-DGOD) aims to train an object detector on a single source domain while generalizing well to diverse unseen target domains, making it s…
PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection
Xiaoran Xu, Jiangang Yang, Wenhui Shi +3
Single-Domain Generalized Object Detection~(S-DGOD) aims to train on a single source domain for robust performance across a variety of unseen target domains by taking advantage of…