1 citations · 1 across the 4 of their papers we have counts for
4 papers
Evolution-Inspired Sample Competition for Deep Neural Network Optimization
Ying Zheng, Yiyi Zhang, Yi Wang +1
Conventional deep network training generally optimizes all samples under a largely uniform learning paradigm, without explicitly modeling the heterogeneous competition among them.…
ProCal: Probability Calibration for Neighborhood-Guided Source-Free Domain Adaptation
Ying Zheng, Yiyi Zhang, Yi Wang +1
Source-Free Domain Adaptation (SFDA) adapts pre-trained models to unlabeled target domains without requiring access to source data. Although state-of-the-art methods leveraging loc…
Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions
Liang Xu, Chengqun Yang, Zili Lin +11
Learning action models from real-world human-centric interaction datasets is important towards building general-purpose intelligent assistants with efficiency. However, most existi…
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition
Ying Zheng, Yiyi Zhang, Yi Wang +1
Source-free domain adaptation in visual emotion recognition (SFDA-VER) is a highly challenging task that requires adapting VER models to the target domain without relying on source…