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20242026
most citedChangeViT: Unleashing Plain Vision Transformers for Change Detection

2 citations · 2 across the 6 of their papers we have counts for

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cs.CV2026

What Makes a Good Visual Representation for Spatial Understanding in MLLMs?

Xiaohu Huang, Yumin Guo, Kai Han

Spatial understanding is a necessary step in moving multimodal large language models (MLLMs) toward reasoning about the 3D physical world. Their visual pretraining data, however, i…

cs.CV2026

Beyond Single Expert: Harmonizing Diverse Visual Priors in MLLMs for Spatial Understanding

Xiao Lin, Xiaohu Huang, Kai Han

Multimodal Large Language Models (MLLMs) have demonstrated substantial promise in spatial understanding. Existing works typically incorporate prior knowledge extracted from a pre-t…

cs.CV2026

OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation

Donghao Zhou, Guisheng Liu, Hao Yang +9

In this work, we study Human-Object Interaction Video Generation (HOIVG), which aims to synthesize high-quality human-object interaction videos conditioned on text, reference image…

cs.CV2025

JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editing

Xiaohu Huang, Haoyang He, Hao Zhou +3

In this paper, we present JoVA, a streamlined framework that unifies joint video-audio generation and editing. While existing methods often rely on fragmented, task-specific archit…

cs.CV2025

3DRS: MLLMs Need 3D-Aware Representation Supervision for Scene Understanding

Xiaohu Huang, Jingjing Wu, Qunyi Xie +1

Recent advances in scene understanding have leveraged multimodal large language models (MLLMs) for 3D reasoning by capitalizing on their strong 2D pretraining. However, the lack of…

cs.CV2024

PruneVid: Visual Token Pruning for Efficient Video Large Language Models

Xiaohu Huang, Hao Zhou, Kai Han

In this paper, we introduce PruneVid, a visual token pruning method designed to enhance the efficiency of multi-modal video understanding. Large Language Models (LLMs) have shown p…

cs.CV2024★ 2 cited

ChangeViT: Unleashing Plain Vision Transformers for Change Detection

Duowang Zhu, Xiaohu Huang, Haiyan Huang +2

Change detection in remote sensing images is essential for tracking environmental changes on the Earth's surface. Despite the success of vision transformers (ViTs) as backbones in…