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20242026
most citedVMBench: A Benchmark for Perception-Aligned Video Motion Generation

1 citations · 2 across the 14 of their papers we have counts for

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cs.CV2026

Omni-WorldBench: Towards a Comprehensive Interaction-Centric Evaluation for World Models

Meiqi Wu, Zhixin Cai, Fufangchen Zhao +13

Video--based world models have emerged along two dominant paradigms: video generation and 3D reconstruction. However, existing evaluation benchmarks either focus narrowly on visual…

cs.CV2025

ImagerySearch: Adaptive Test-Time Search for Video Generation Beyond Semantic Dependency Constraints

Meiqi Wu, Jiashu Zhu, Xiaokun Feng +7

Video generation models have achieved remarkable progress, particularly excelling in realistic scenarios; however, their performance degrades notably in imaginative scenarios. Thes…

cs.CV2025

UNIV: Unified Foundation Model for Infrared and Visible Modalities

Fangyuan Mao, Shuo Wang, Jilin Mei +6

Joint RGB-infrared perception is essential for achieving robustness under diverse weather and illumination conditions. Although foundation models excel within single modalities, th…

cs.CV2025

VS-LLM: Visual-Semantic Depression Assessment based on LLM for Drawing Projection Test

Meiqi Wu, Yaxuan Kang, Xuchen Li +5

The Drawing Projection Test (DPT) is an essential tool in art therapy, allowing psychologists to assess participants' mental states through their sketches. Specifically, through sk…

cs.CV2025

Stochastic Self-Guidance for Training-Free Enhancement of Diffusion Models

Chubin Chen, Jiashu Zhu, Xiaokun Feng +7

Classifier-free Guidance (CFG) is a widely used technique in modern diffusion models for enhancing sample quality and prompt adherence. However, through an empirical analysis on Ga…

cs.CV2025

Omni-Effects: Unified and Spatially-Controllable Visual Effects Generation

Fangyuan Mao, Aiming Hao, Jintao Chen +7

Visual effects (VFX) are essential visual enhancements fundamental to modern cinematic production. Although video generation models offer cost-efficient solutions for VFX productio…

cs.CV2025

ATCTrack: Aligning Target-Context Cues with Dynamic Target States for Robust Vision-Language Tracking

X. Feng, S. Hu, X. Li +5

Vision-language tracking aims to locate the target object in the video sequence using a template patch and a language description provided in the initial frame. To achieve robust t…

cs.CV2025★ 1 cited

VMBench: A Benchmark for Perception-Aligned Video Motion Generation

Xinran Ling, Chen Zhu, Meiqi Wu +7

Video generation has advanced rapidly, improving evaluation methods, yet assessing video's motion remains a major challenge. Specifically, there are two key issues: 1) current moti…

cs.CV2024

Enhancing Vision-Language Tracking by Effectively Converting Textual Cues into Visual Cues

X. Feng, D. Zhang, S. Hu +5

Vision-Language Tracking (VLT) aims to localize a target in video sequences using a visual template and language description. While textual cues enhance tracking potential, current…

cs.CV2024

Finger in Camera Speaks Everything: Unconstrained Air-Writing for Real-World

Meiqi Wu, Kaiqi Huang, Yuanqiang Cai +3

Air-writing is a challenging task that combines the fields of computer vision and natural language processing, offering an intuitive and natural approach for human-computer interac…

cs.CV2024

How Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking

Xuchen Li, Shiyu Hu, Xiaokun Feng +4

Vision-language tracking (VLT) extends traditional single object tracking by incorporating textual information, providing semantic guidance to enhance tracking performance under ch…

cs.CV2024★ 1 cited

DTVLT: A Multi-modal Diverse Text Benchmark for Visual Language Tracking Based on LLM

Xuchen Li, Shiyu Hu, Xiaokun Feng +4

Visual language tracking (VLT) has emerged as a cutting-edge research area, harnessing linguistic data to enhance algorithms with multi-modal inputs and broadening the scope of tra…

cs.CV2024

Visual Language Tracking with Multi-modal Interaction: A Robust Benchmark

Xuchen Li, Shiyu Hu, Xiaokun Feng +4

Visual Language Tracking (VLT) enhances tracking by mitigating the limitations of relying solely on the visual modality, utilizing high-level semantic information through language.…

cs.CV2024

DTLLM-VLT: Diverse Text Generation for Visual Language Tracking Based on LLM

Xuchen Li, Xiaokun Feng, Shiyu Hu +4

Visual Language Tracking (VLT) enhances single object tracking (SOT) by integrating natural language descriptions from a video, for the precise tracking of a specified object. By l…