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20212024
most citedUnsupervised Low-Light Image Enhancement via Histogram Equalization Prior

25 citations · 82 across the 23 of their papers we have counts for

collaborators

20 papers

cs.CV2024

Cross-video Identity Correlating for Person Re-identification Pre-training

Jialong Zuo, Ying Nie, Hanyu Zhou +5

Recent researches have proven that pre-training on large-scale person images extracted from internet videos is an effective way in learning better representations for person re-ide…

cs.CV20243 cited

Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM

Huaxin Zhang, Xiaohao Xu, Xiang Wang +6

Towards open-ended Video Anomaly Detection (VAD), existing methods often exhibit biased detection when faced with challenging or unseen events and lack interpretability. To address…

cs.CV20241 cited

Open-Vocabulary Semantic Segmentation with Image Embedding Balancing

Xiangheng Shan, Dongyue Wu, Guilin Zhu +3

Open-vocabulary semantic segmentation is a challenging task, which requires the model to output semantic masks of an image beyond a close-set vocabulary. Although many efforts have…

cs.CV2024

Tunnel Try-on: Excavating Spatial-temporal Tunnels for High-quality Virtual Try-on in Videos

Zhengze Xu, Mengting Chen, Zhao Wang +6

Video try-on is a challenging task and has not been well tackled in previous works. The main obstacle lies in preserving the details of the clothing and modeling the coherent motio…

cs.CV2024

REPAIR: Rank Correlation and Noisy Pair Half-replacing with Memory for Noisy Correspondence

Ruochen Zheng, Jiahao Hong, Changxin Gao +1

The presence of noise in acquired data invariably leads to performance degradation in cross-modal matching. Unfortunately, obtaining precise annotations in the multimodal field is…

cs.CV20242 cited

GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection

Huaxin Zhang, Xiang Wang, Xiaohao Xu +6

In recent years, video anomaly detection has been extensively investigated in both unsupervised and weakly supervised settings to alleviate costly temporal labeling. Despite signif…