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20222026
most citedRethinking the Learning Paradigm for Facial Expression Recognition

5 citations · 12 across the 11 of their papers we have counts for

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cs.CV2026

Hypergraph Normal World Models for Logical Visual Anomaly Detection

Weizhi Nie, Zibo Xu, Weijie Wang +1

Visual anomaly detection is often deployed with only normal training images. Most one-class detectors map test patches or features to a normal reference distribution. This works we…

cs.CV2026

Ask4VG: Risk-Aware Question Selection for Reducing Prior-Driven Answers in Medical VQA

Xiaorong Zhu, Qiang Li, Zibo Xu +2

Medical visual question answering requires models to ground their responses in image evidence, because visually unsupported answers can mislead downstream interpretation. However,…

cs.CV2023★ 1 cited

T2TD: Text-3D Generation Model based on Prior Knowledge Guidance

Weizhi Nie, Ruidong Chen, Weijie Wang +2

In recent years, 3D models have been utilized in many applications, such as auto-driver, 3D reconstruction, VR, and AR. However, the scarcity of 3D model data does not meet its pra…

cs.CV2023★ 3 cited

RFR-WWANet: Weighted Window Attention-Based Recovery Feature Resolution Network for Unsupervised Image Registration

Mingrui Ma, Tao Wang, Lei Song +2

The Swin transformer has recently attracted attention in medical image analysis due to its computational efficiency and long-range modeling capability. Owing to these properties, t…

cs.CV2023★ 3 cited

Unsupervised Deep Probabilistic Approach for Partial Point Cloud Registration

Guofeng Mei, Hao Tang, Xiaoshui Huang +5

Deep point cloud registration methods face challenges to partial overlaps and rely on labeled data. To address these issues, we propose UDPReg, an unsupervised deep probabilistic r…

cs.CV2022★ 5 cited

Rethinking the Learning Paradigm for Facial Expression Recognition

Weijie Wang, Bo Li, Nicu Sebe +1

Due to the subjective crowdsourcing annotations and the inherent inter-class similarity of facial expressions, the real-world Facial Expression Recognition (FER) datasets usually e…