Boxes2Pixels distills noisy SAM pseudo-masks into a compact DINOv2-based student with auxiliary localization and one-sided self-correction, delivering +6.97 anomaly mIoU and +9.71 binary IoU gains over baselines on wind turbine data with 80% fewer parameters.
Learning transferable visual models from natural language supervision
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DRG-Font generates stylistically consistent glyphs from few references by decomposing style and content via contrastive disentanglement, dynamic reference selection, and multi-scale fusion blocks.
Visual representations in VLMs converge quickly to stable low-complexity forms while text continues evolving, with task-dependent needs for sustained image token access.
citing papers explorer
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Boxes2Pixels: Learning Defect Segmentation from Noisy SAM Masks
Boxes2Pixels distills noisy SAM pseudo-masks into a compact DINOv2-based student with auxiliary localization and one-sided self-correction, delivering +6.97 anomaly mIoU and +9.71 binary IoU gains over baselines on wind turbine data with 80% fewer parameters.
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DRG-Font: Dynamic Reference-Guided Few-shot Font Generation via Contrastive Style-Content Disentanglement
DRG-Font generates stylistically consistent glyphs from few references by decomposing style and content via contrastive disentanglement, dynamic reference selection, and multi-scale fusion blocks.
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Do Vision Language Models Need to Process Image Tokens?
Visual representations in VLMs converge quickly to stable low-complexity forms while text continues evolving, with task-dependent needs for sustained image token access.