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arXiv — cs.AI preprintsInternational19 October 2026

Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding

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arXiv:2412.00684v3 Announce Type: replace-cross Abstract: Visual grounding aims to localize the image regions based on a textual query. Given the difficulty of large-scale data curation, we investigate how to effectively learn visual grounding under data-scarce settings in this paper. To address the data scarcity, we propose a novel framework, POBF (Paint Outside the Box and Filter). POBF synthesizes images by inpainting outside the box, tackling a label misalignment issue encountered in previous works. Furthermore, POBF leverages an innovative filtering scheme to select the most effective tra
— arXiv — cs.AI preprints

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