87 citations · 115 across the 6 of their papers we have counts for
7 papers · 1 filter
Towards Control-Centric Representations in Reinforcement Learning from Images
Chen Liu, Hongyu Zang, Xin Li +5
Image-based Reinforcement Learning is a practical yet challenging task. A major hurdle lies in extracting control-centric representations while disregarding irrelevant information.…
Enhancing the Authenticity of Rendered Portraits with Identity-Consistent Transfer Learning
Luyuan Wang, Yiqian Wu, Yongliang Yang +2
Despite rapid advances in computer graphics, creating high-quality photo-realistic virtual portraits is prohibitively expensive. Furthermore, the well-know ''uncanny valley'' effec…
Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning
Yong Lin, Chen Liu, Chenlu Ye +3
Modern deep learning heavily relies on large labeled datasets, which often comse with high costs in terms of both manual labeling and computational resources. To mitigate these cha…
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification
Ziqi Yang, Zhongyu Li, Chen Liu +7
Convolutional neural networks excel in histopathological image classification, yet their pixel-level focus hampers explainability. Conversely, emerging graph convolutional networks…
BAVS: Bootstrapping Audio-Visual Segmentation by Integrating Foundation Knowledge
Chen Liu, Peike Li, Hu Zhang +4
Given an audio-visual pair, audio-visual segmentation (AVS) aims to locate sounding sources by predicting pixel-wise maps. Previous methods assume that each sound component in an a…
Audio-Visual Segmentation by Exploring Cross-Modal Mutual Semantics
Chen Liu, Peike Li, Xingqun Qi +4
The audio-visual segmentation (AVS) task aims to segment sounding objects from a given video. Existing works mainly focus on fusing audio and visual features of a given video to ac…