collaborators

12 papers

cs.CV2026

UniSpace: Unified Visual Representation and Scalable Multimodal Modeling

Jinbo Yan, Limeng Qiao, Jie Qin +3

Semantic vision encoders have become a central visual interface for multimodal understanding and semantic conditioning in image generation. However, their final tokens discard fine…

cs.CV2026

HoloCount: A Holistic Visual Counting Benchmark for MLLMs

Jinhong Deng, Limeng Qiao, Guanglu Wan

Visual counting is a fundamental pillar of multimodal intelligence, requiring a seamless integration of fine-grained grounding and spatial reasoning. While Multimodal Large Languag…

cs.CV2026

X2SAM: Any Segmentation in Images and Videos

Hao Wang, Limeng Qiao, Chi Zhang +4

Multimodal Large Language Models (MLLMs) have demonstrated strong image-level visual understanding and reasoning, yet their pixel-level perception across both images and videos rem…

cs.CV2026

GeoAlign: Geometric Feature Realignment for MLLM Spatial Reasoning

Zhaochen Liu, Limeng Qiao, Guanglu Wan +1

Multimodal large language models (MLLMs) have exhibited remarkable performance in various visual tasks, yet still struggle with spatial reasoning. Recent efforts mitigate this by i…

cs.CV2026

UniComp: Rethinking Video Compression Through Informational Uniqueness

Chao Yuan, Shimin Chen, Minliang Lin +3

Distinct from attention-based compression methods, this paper presents an information uniqueness driven video compression framework, termed UniComp, which aims to maximize the info…

cs.CV2026

X-SAM: From Segment Anything to Any Segmentation

Hao Wang, Limeng Qiao, Zequn Jie +6

Large Language Models (LLMs) demonstrate strong capabilities in broad knowledge representation, yet they are inherently deficient in pixel-level perceptual understanding. Although…