activity
20232026
most citedDVIS++: Improved Decoupled Framework for Universal Video Segmentation

3 citations · 4 across the 18 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.CV2025

The 1st Solution for 7th LSVOS RVOS Track: SaSaSa2VA

Quanzhu Niu, Dengxian Gong, Shihao Chen +6

Referring video object segmentation (RVOS) requires segmenting and tracking objects in videos conditioned on natural-language expressions, demanding fine-grained understanding of b…

cs.CV2025

LSVOS 2025 Challenge Report: Recent Advances in Complex Video Object Segmentation

Chang Liu, Henghui Ding, Kaining Ying +46

This report presents an overview of the 7th Large-scale Video Object Segmentation (LSVOS) Challenge held in conjunction with ICCV 2025. Besides the two traditional tracks of LSVOS…

cs.CV2025

Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs

Haochen Wang, Yuhao Wang, Tao Zhang +13

While Multimodal Large Language Models (MLLMs) excel at holistic understanding, they struggle in capturing the dense world with complex scenes, requiring fine-grained analysis of i…

cs.CV2025

Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation

Quanzhu Niu, Yikang Zhou, Shihao Chen +2

Video Instance Segmentation (VIS) fundamentally struggles with pervasive challenges including object occlusions, motion blur, and appearance variations during temporal association.…

cs.CV2025

DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World

Xiangtai Li, Tao Zhang, Yanwei Li +13

Multimodal Large Language Models (MLLMs) demonstrate a complex understanding of scenes, benefiting from large-scale and high-quality datasets. Most existing caption datasets lack t…

cs.CV2025

Dense360: Dense Understanding from Omnidirectional Panoramas

Yikang Zhou, Tao Zhang, Dizhe Zhang +3

Multimodal Large Language Models (MLLMs) require comprehensive visual inputs to achieve dense understanding of the physical world. While existing MLLMs demonstrate impressive world…

cs.CV2025

An Empirical Study of GPT-4o Image Generation Capabilities

Sixiang Chen, Jinbin Bai, Zhuoran Zhao +16

The landscape of image generation has rapidly evolved, from early GAN-based approaches to diffusion models and, most recently, to unified generative architectures that seek to brid…

cs.CV2025

Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs

Yikang Zhou, Tao Zhang, Shilin Xu +7

Recent advancements in multimodal large language models (MLLM) have shown a strong ability in visual perception, reasoning abilities, and vision-language understanding. However, th…