Visual Memory and Textual Alignment for Cross-Modal Few-Shot Segmentation
Few-shot segmentation (FSS) aims to segment target objects with limited annotated examples. Recent studies have begun to explore large foundation models to improve generalization for this task. In particular, SAM 3 provides strong visual representations and supports text-guided segmentation. However, its performance remains limited in specialized domains, where semantic prompts and visual representations are often poorly aligned. To address this challenge, we propose ViTA-SAM, a framework built upon SAM 3 that integrates visual memory and textual features through cross-modal alignment. Specifically, we construct a visual memory module that encodes support features together with their corr...
| Authors | Tianqi Wei, Zhi Chen, Xin Yu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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