attention analysis 1patch-level semantics 1training-free methods 1vision-language models 1zero-shot segmentation 1
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cs.CV2026
TraceCLIP: Recovering Local Semantics from Patch-to-CLS Contributions
Xinran Liu, Shouqian Shi, Yutong Chen +3
The paper presents TraceCLIP, a training‑free method that extracts patch‑level semantic information from CLIP's CLS attention output to improve zero‑shot dense vision‑language task…
cs.CV2026
Efficient Transferable Optimal Transport via Min-Sliced Transport Plans
Xinran Liu, Elaheh Akbari, Rocio Diaz Martin +2
Optimal Transport (OT) offers a powerful framework for finding correspondences between distributions and addressing matching and alignment problems in various areas of computer vis…
cs.CV2024
Equivariant vs. Invariant Layers: A Comparison of Backbone and Pooling for Point Cloud Classification
Abihith Kothapalli, Ashkan Shahbazi, Xinran Liu +2
Learning from set-structured data, such as point clouds, has gained significant attention from the machine learning community. Geometric deep learning provides a blueprint for desi…