AI RESEARCH
DSAA: Dual-Stage Attribute Activation for Fine-grained Open Vocabulary Detection
arXiv CS.CV
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ArXi:2605.18023v1 Announce Type: new Open-Vocabulary Object Detection (OVD) models break the limitations of closed-set detection, enabling the iden- tification of unseen categories through natural language prompts. However, they exhibit notable limitations in fine- grained detection tasks involving attributes like color, ma- terial, and texture. We attribute this performance bottle- neck in OVD models to a core issue: when category sig- nals dominate, OVD models tend to marginalize attribute information during inference.