42 citations · 127 across the 11 of their papers we have counts for
14 papers · 1 filter
Category-Adaptive Label Discovery and Noise Rejection for Multi-label Image Recognition with Partial Positive Labels
Tao Pu, Qianru Lao, Hefeng Wu +2
As a promising solution of reducing annotation cost, training multi-label models with partial positive labels (MLR-PPL), in which merely few positive labels are known while other a…
Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels
Tao Pu, Tianshui Chen, Hefeng Wu +1
Training the multi-label image recognition models with partial labels, in which merely some labels are known while others are unknown for each image, is a considerably challenging…
AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition
Tao Pu, Tianshui Chen, Yuan Xie +2
Recognizing human emotion/expressions automatically is quite an expected ability for intelligent robotics, as it can promote better communication and cooperation with humans. Curre…
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting
Lingbo Liu, Jiaqi Chen, Hefeng Wu +3
Crowd counting is a fundamental yet challenging task, which desires rich information to generate pixel-wise crowd density maps. However, most previous methods only used the limited…
Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition
Tianshui Chen, Liang Lin, Riquan Chen +2
Recognizing multiple labels of an image is a practical yet challenging task, and remarkable progress has been achieved by searching for semantic regions and exploiting label depend…
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
Yuan Xie, Tianshui Chen, Tao Pu +2
Data inconsistency and bias are inevitable among different facial expression recognition (FER) datasets due to subjective annotating process and different collecting conditions. Re…