MARS-CLIP: Multi-Resolution and Attention Refined Zero-Shot Image Segmentation
Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in zero-shot transfer but often struggles with dense prediction tasks due to low spatial resolution and the loss of structural information. To address these limitations, we propose MARS-CLIP (Multi-resolution and Attention Refined Segmentation for CLIP), a novel framework for zero-shot semantic segmentation. Our approach introduces two key strategies: (i) a multi-resolution feature extraction module that fuses local fine-grained features with global context to overcome input resolution constraints, and (ii) an attention refinement mechanism that injects spatial and color biases from intermediate layers...
| Authors | Nagito Saito, Shintaro Ito, Koichi Ito et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 September 2026 |
| Last updated at source | 8 September 2026 |
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