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cs.CV2026
Heuristic-inspired Reasoning Priors Facilitate Data-Efficient Referring Object Detection
Xu Zhang, Zhe Chen, Jing Zhang +1
Most referring object detection (ROD) models, especially the modern grounding detectors, are designed for data-rich conditions, yet many practical deployments, such as robotics, au…
cs.CV2026
LAB-Det: Language as a Domain-Invariant Bridge for Training-Free One-Shot Domain Generalization in Object Detection
Xu Zhang, Zhe Chen, Jing Zhang +1
Foundation object detectors such as GLIP and Grounding DINO excel on general-domain data but often degrade in specialized and data-scarce settings like underwater imagery or indust…
cs.CV2025
Unified Unsupervised Anomaly Detection via Matching Cost Filtering
Zhe Zhang, Mingxiu Cai, Gaochang Wu +5
Unsupervised anomaly detection (UAD) aims to identify image- and pixel-level anomalies using only normal training data, with wide applications such as industrial inspection and med…