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20232026
most citedLearning Correlation Structures for Vision Transformers

2 citations · 2 across the 4 of their papers we have counts for

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cs.CV2026

SpaCeFormer: Fast Proposal-Free Open-Vocabulary 3D Instance Segmentation

Chris Choy, Junha Lee, Chunghyun Park +2

Open-vocabulary 3D instance segmentation is a core capability for robotics and AR/VR, but prior methods trade one bottleneck for another: multi-stage 2D+3D pipelines aggregate foun…

cs.CV2026

Cog3DMap: Multi-View Vision-Language Reasoning with 3D Cognitive Maps

Chanyoung Gwak, Yoonwoo Jeong, Byungwoo Jeon +3

Precise spatial understanding from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs), as their visual representations are predominantly…

cs.CV20242 cited

Learning Correlation Structures for Vision Transformers

Manjin Kim, Paul Hongsuck Seo, Cordelia Schmid +1

We introduce a new attention mechanism, dubbed structural self-attention (StructSA), that leverages rich correlation patterns naturally emerging in key-query interactions of attent…

cs.CV2024

MoReVQA: Exploring Modular Reasoning Models for Video Question Answering

Juhong Min, Shyamal Buch, Arsha Nagrani +2

This paper addresses the task of video question answering (videoQA) via a decomposed multi-stage, modular reasoning framework. Previous modular methods have shown promise with a si…

cs.CV2023

Efficient Semantic Matching with Hypercolumn Correlation

Seungwook Kim, Juhong Min, Minsu Cho

Recent studies show that leveraging the match-wise relationships within the 4D correlation map yields significant improvements in establishing semantic correspondences - but at the…