activity
20162022
most citedMulti-label Image Recognition by Recurrently Discovering Attentional Regions

53 citations · 197 across the 12 of their papers we have counts for

collaborators

21 papers

cs.CV20221 cited

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…

cs.CV2022

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…

cs.CV20201 cited

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…

cs.CV202013 cited

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…

cs.CV20204 cited

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…

cs.CV20208 cited

Fine-Grained Image Captioning with Global-Local Discriminative Objective

Jie Wu, Tianshui Chen, Hefeng Wu +3

Significant progress has been made in recent years in image captioning, an active topic in the fields of vision and language. However, existing methods tend to yield overly general…