ARTA: Adaptive Mixed-Resolution Token Allocation for Efficient Dense Feature Extraction

1. 1Start with low-resolution tokens and use a lightweight allocator to predict regions requiring more fine tokens
2. 2Iteratively predict semantic boundary scores and allocate additional tokens to patches above a low threshold
3. 3Refine token allocation through multiple iterations to achieve efficient dense feature extraction

Computer vision engineers and researchers on a team can benefit from ARTA as it improves the efficiency of dense feature extraction, while product managers can consider its potential for applications in image and video analysis

💡 Adaptive token allocation can significantly improve the efficiency of dense feature extraction in vision transformers

💡 Efficient dense feature extraction with ARTA, a mixed-resolution vision transformer