6 citations · 9 across the 12 of their papers we have counts for
15 papers
RSAgent: Learning to Reason and Act for Text-Guided Segmentation via Multi-Turn Tool Invocations
Xingqi He, Yujie Zhang, Shuyong Gao +6
Text-guided object segmentation requires both cross-modal reasoning and pixel grounding abilities. Most recent methods treat text-guided segmentation as one-shot grounding, where t…
Collaborative Reconstruction and Repair for Multi-class Industrial Anomaly Detection
Qishan Wang, Haofeng Wang, Shuyong Gao +5
Industrial anomaly detection is a challenging open-set task that aims to identify unknown anomalous patterns deviating from normal data distribution. To avoid the significant memor…
Commonality in Few: Few-Shot Multimodal Anomaly Detection via Hypergraph-Enhanced Memory
Yuxuan Lin, Hanjing Yan, Xuan Tong +6
Few-shot multimodal industrial anomaly detection is a critical yet underexplored task, offering the ability to quickly adapt to complex industrial scenarios. In few-shot settings,…
Search is All You Need for Few-shot Anomaly Detection
Qishan Wang, Jia Guo, Shuyong Gao +5
Few-shot anomaly detection (FSAD) has emerged as a crucial yet challenging task in industrial inspection, where normal distribution modeling must be accomplished with only a few no…
HSS-IAD: A Heterogeneous Same-Sort Industrial Anomaly Detection Dataset
Qishan Wang, Shuyong Gao, Junjie Hu +4
Multi-class Unsupervised Anomaly Detection algorithms (MUAD) are receiving increasing attention due to their relatively low deployment costs and improved training efficiency. Howev…
Scoring, Remember, and Reference: Catching Camouflaged Objects in Videos
Yuang Feng, Shuyong Gao, Fuzhen Yan +4
Video Camouflaged Object Detection (VCOD) aims to segment objects whose appearances closely resemble their surroundings, posing a challenging and emerging task. Existing vision mod…