activity
20242026
collaborators

45 papers

cs.CV2026

Verus-Insight: Towards Explainable Artifact Detection in AI-Generated Videos

Zhuoran Zhang, Yang Shi, Qixun Wang +11

Recent advances in video generation have made synthetic videos increasingly realistic, placing greater demands on reliable AI-generated video detection. Existing artifact-based det…

cs.CV2026

Mise-en-Video: Fine-Grained 3D Control for Multi-Shot Video Generation

Yingshuang Zou, Xiaoyu Shi, Yawen Luo +8

Recent advances in text-to-video generation have enabled high-fidelity single-shot synthesis, yet practical storytelling creation requires multi-shot videos with both strong inter-…

cs.CV2026

PIGEONS: Incremental Long-Video Captioning with Persistent Identity Gallery and Evolving Overarching Narrative Summary

Xinlong Chen, Weihong Lin, Yuanxing Zhang +9

Detailed video captioning has become an essential semantic interface for multi-modal understanding and generation. While existing methods mainly target short videos, extending them…

cs.CV2026

PercepCap: Video Captioner with Structured Spatio-Temporal Perception

Yifan Xu, Zihao Wang, Zhixiao Wang +6

Video captioning requires fine-grained spatio-temporal understanding of videos, including spatial perception of where objects are located and temporal perception of when events occ…

cs.CV2026

ContextMaster: Interactive Multi-Shot Video Creation via Fixed-Budget Sparse Context Routing

Xu Guo, Zhengxuan Wei, Xinghui Li +11

Recent video models increasingly support generation, reference conditioning, and editing within a single model, yet typically expose them as separate operations over fixed inputs.…

cs.CV2026

Beacon: Knowing When and How to Perform Agentic Visual Reasoning

Qixun Wang, Yang Shi, Letian Cheng +11

The fundamental goal of agentic visual reasoning is to improve the success rate of multimodal large language models (MLLMs) on complex tasks. We rethink agentic visual reasoning th…

cs.CV2026

ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships

Xinyu Liu, Shihao Li, Weihong Lin +10

Recent diffusion-based video generation models have made significant progress in multi-reference image-conditioned video editing. However, existing methods still struggle to coordi…

cs.CV2026

MemLearner: Learning to Query Context memory for Video World Models

Jiwen Yu, Jianxiong Gao, Jianhong Bai +7

Video World Models are interactive video generation models that predict future world states based on user actions and history video frames. A critical challenge in video world mode…

cs.CV2026

VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization

Junhao Cheng, Liang Hou, Tianxiong Zhong +4

The recent "Reasoning with Video" paradigm utilizes Video Generation Models (VGMs) to generate temporally coherent visual trajectories to complete reasoning tasks. Although state-o…

cs.AI2026

Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing

Yuxiao Ye, Haoran He, Fangyuan Kong +4

Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain confined to single-turn setting…

cs.CV2026

Geometry-Aware Implicit Memory for Video World Models

Zhengxuan Wei, Xu Guo, Xinghui Li +8

Video world models aim to simulate controllable visual environments, but long-horizon rollouts depend on what the model remembers after observations leave its native context window…

cs.CV2026

DecMem: Towards Minute-Long Consistent World Generation with Decoupled Memory

Zhenhao Yang, Xiaoshi Wu, Zhengyao Lv +5

Recent advances in video generative models have promoted rapid progress in controllable world models. However, maintaining fine-grained spatio-temporal consistency under long-horiz…

cs.CV2026

LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV

Tengfei Liu, Yang Shi, Xuanyu Zhu +17

Audio-visual generation is rapidly advancing from short clips to minute-long content, while existing evaluation protocols remain largely confined to short-form settings. Existing b…

cs.CV2026

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models

DataFlow Team, Bohan Zeng, Daili Hua +39

World models have garnered significant attention as a promising research direction in artificial intelligence, yet a clear and unified definition remains lacking. In this paper, we…

cs.CV2026

Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos

Yuqi Tang, Yang Shi, Zhuoran Zhang +21

Recent video generative models have greatly improved the realism of AI-generated videos, yet their outputs still exhibit artifacts such as temporal inconsistencies, structural dist…

cs.CV2026

Think, then Score: Decoupled Reasoning and Scoring for Video Reward Modeling

Yuan Wang, Ouxiang Li, Yulong Xu +8

Recent advances in generative video models are increasingly driven by post-training and test-time scaling, both of which critically depend on the quality of video reward models (RM…

cs.CV2026

LIVE: Leveraging Image Manipulation Priors for Instruction-based Video Editing

Weicheng Wang, Zhicheng Zhang, Zhongqi Zhang +6

Video editing aims to modify input videos according to user intent. Recently, end-to-end training methods have garnered widespread attention, constructing paired video editing data…

cs.CV2026

Beyond the Golden Data: Resolving the Motion-Vision Quality Dilemma via Timestep Selective Training

Xiangyang Luo, Qingyu Li, Yuming Li +6

Recent advances in video generation models have achieved impressive results. However, these models heavily rely on the use of high-quality data that combines both high visual quali…

cs.CV2026

Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models

Kaijin Chen, Dingkang Liang, Xin Zhou +4

Video world models have shown immense potential in simulating the physical world, yet existing memory mechanisms primarily treat environments as static canvases. When dynamic subje…

cs.CV2026

Less Gaussians, Texture More: 4K Feed-Forward Textured Splatting

Yixing Lao, Xuyang Bai, Xiaoyang Wu +7

Existing feed-forward 3D Gaussian Splatting methods predict pixel-aligned primitives, leading to a quadratic growth in primitive count as resolution increases. This fundamentally l…

cs.CV2026

Kling-MotionControl Technical Report

Kling Team, Jialu Chen, Yikang Ding +21

Character animation aims to generate lifelike videos by transferring motion dynamics from a driving video to a reference image. Recent strides in generative models have paved the w…

cs.CV2026

3D-Aware Implicit Motion Control for View-Adaptive Human Video Generation

Zhixue Fang, Xu He, Songlin Tang +5

Existing methods for human motion control in video generation typically rely on either 2D poses or explicit 3D parametric models (e.g., SMPL) as control signals. However, 2D poses…

cs.CV2026

Semantic Routing: Exploring Multi-Layer LLM Feature Weighting for Diffusion Transformers

Bozhou Li, Yushuo Guan, Haolin Li +7

Recent DiT-based text-to-image models increasingly adopt LLMs as text encoders, yet text conditioning remains largely static and often utilizes only a single LLM layer, despite pro…

cs.CV2026

TimeChat-Captioner: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions

Linli Yao, Yuancheng Wei, Yaojie Zhang +12

This paper proposes Omni Dense Captioning, a novel task designed to generate continuous, fine-grained, and structured audio-visual narratives with explicit timestamps. To ensure de…