activity
20232026
most citedRGB-D Video Object Segmentation via Enhanced Multi-store Feature Memory

4 citations · 10 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV2026

VIABench: A Comprehensive Video Benchmark Collected from Blind Individuals for Visual Impairment Assistance

Yunfeng Liu, Yuandong Yang, Jiarui Han +5

Visually impaired individuals (VIIs) encounter significant daily challenges due to limited access to visual information. Although Multimodal Large Language Models (MLLMs) have achi…

cs.CV2026

VL-UniTrack: A Unified Framework with Visual-Language Prompts for UAV-Ground Visual Tracking

Boyue Xu, Ruichao Hou, Tongwei Ren +1

UAV-ground visual tracking (UGVT) aims to simultaneously track the same object from both the UAV and the ground view. However, existing two-stream methods suffer from isolated feat…

cs.CV2026

VMonarch: Efficient Video Diffusion Transformers with Structured Attention

Cheng Liang, Haoxian Chen, Liang Hou +4

The quadratic complexity of the attention mechanism severely limits the context scalability of Video Diffusion Transformers (DiTs). We find that the highly sparse spatio-temporal a…

cs.CV2025

SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation

Jiaming Zhang, Shengming Cao, Rui Li +8

Preserving first-frame identity while ensuring precise motion control is a fundamental challenge in human image animation. The Image-to-Motion Binding process of the dominant Refer…

cs.CV2025

SAM 2++: Tracking Anything at Any Granularity

Jiaming Zhang, Cheng Liang, Yichun Yang +7

Due to the varying granularity of target states across different tasks, most existing trackers are tailored to a single task, which specificity limits their generalization, prevent…

cs.CV2025

MotionRAG: Motion Retrieval-Augmented Image-to-Video Generation

Chenhui Zhu, Yilu Wu, Shuai Wang +2

Image-to-video generation has made remarkable progress with the advancements in diffusion models, yet generating videos with realistic motion remains highly challenging. This diffi…