AVA-VLM reduces visual-token usage by 69% while improving PPE-violation F1 by 13 points over direct-QA baselines by training a VLM to adaptively crop high-resolution local regions from a downsampled global image.
Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
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AVA-VLM: Adaptive Visual Attention-Vision Language Model for In-the-Wild Construction Site Monitoring
AVA-VLM reduces visual-token usage by 69% while improving PPE-violation F1 by 13 points over direct-QA baselines by training a VLM to adaptively crop high-resolution local regions from a downsampled global image.