AI RESEARCH
PET-DINO: Unifying Visual Cues into Grounding DINO with Prompt-Enriched Training
arXiv CS.CV
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ArXi:2604.00503v1 Announce Type: new Open-Set Object Detection (OSOD) enables recognition of novel categories beyond fixed classes but faces challenges in aligning text representations with complex visual concepts and the scarcity of image-text pairs for rare categories. This results in suboptimal performance in specialized domains or with complex objects. Recent visual-prompted methods partially address these issues but often involve complex multi-modal designs and multi-stage optimizations, prolonging the development cycle. Additionally, effective