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cs.CV2024★ 1 cited
Revisiting Energy-Based Model for Out-of-Distribution Detection
Yifan Wu, Xichen Ye, Songmin Dai +4
Out-of-distribution (OOD) detection is an essential approach to robustifying deep learning models, enabling them to identify inputs that fall outside of their trained distribution.…
cs.CV2024★ 1 cited
Active Negative Loss: A Robust Framework for Learning with Noisy Labels
Xichen Ye, Yifan Wu, Yiqi Wang +3
Deep supervised learning has achieved remarkable success across a wide range of tasks, yet it remains susceptible to overfitting when confronted with noisy labels. To address this…
cs.CV2024
DuPL: Dual Student with Trustworthy Progressive Learning for Robust Weakly Supervised Semantic Segmentation
Yuanchen Wu, Xichen Ye, Kequan Yang +2
Recently, One-stage Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained increasing interest due to simplification over its cumbersome multi-stage coun…