22 citations · 50 across the 22 of their papers we have counts for
24 papers
Beyond Hazard Resemblance: Contrastive Event Adjudication for Training-Free Video Anomaly Detection
Wenti Yin, Xiang Wang, Huaxin Zhang +4
Video anomaly detection (VAD) aims to identify and temporally localize abnormal events in videos. Supervised methods learn anomaly decision boundaries from target-domain annotation…
FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling
Jialong Zuo, Haotong Zuo, Shiwei Zhang +5
Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-form, multi-scene visual nar…
DreamVideo-Omni: Omni-Motion Controlled Multi-Subject Video Customization with Latent Identity Reinforcement Learning
Yujie Wei, Xinyu Liu, Shiwei Zhang +12
While large-scale diffusion models have revolutionized video synthesis, achieving precise control over both multi-subject identity and multi-granularity motion remains a significan…
DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
Haoyou Deng, Keyu Yan, Chaojie Mao +4
Recent GRPO-based approaches built on flow matching models have shown remarkable improvements in human preference alignment for text-to-image generation. Nevertheless, they still s…
HBridge: H-Shape Bridging of Heterogeneous Experts for Unified Multimodal Understanding and Generation
Xiang Wang, Zhifei Zhang, He Zhang +11
Recent unified models integrate understanding experts (e.g., LLMs) with generative experts (e.g., diffusion models), achieving strong multimodal performance. However, recent advanc…
Exploiting Discriminative Codebook Prior for Autoregressive Image Generation
Longxiang Tang, Ruihang Chu, Xiang Wang +6
Advanced discrete token-based autoregressive image generation systems first tokenize images into sequences of token indices with a codebook, and then model these sequences in an au…
DFVEdit: Conditional Delta Flow Vector for Zero-shot Video Editing
Lingling Cai, Kang Zhao, Hangjie Yuan +3
The advent of Video Diffusion Transformers (Video DiTs) marks a milestone in video generation. However, directly applying existing video editing methods to Video DiTs often incurs…
UniAnimate-DiT: Human Image Animation with Large-Scale Video Diffusion Transformer
Xiang Wang, Shiwei Zhang, Longxiang Tang +4
This report presents UniAnimate-DiT, an advanced project that leverages the cutting-edge and powerful capabilities of the open-source Wan2.1 model for consistent human image animat…
Taming Consistency Distillation for Accelerated Human Image Animation
Xiang Wang, Shiwei Zhang, Hangjie Yuan +5
Recent advancements in human image animation have been propelled by video diffusion models, yet their reliance on numerous iterative denoising steps results in high inference costs…
DreamRelation: Relation-Centric Video Customization
Yujie Wei, Shiwei Zhang, Hangjie Yuan +8
Relational video customization refers to the creation of personalized videos that depict user-specified relations between two subjects, a crucial task for comprehending real-world…
FreeScale: Unleashing the Resolution of Diffusion Models via Tuning-Free Scale Fusion
Haonan Qiu, Shiwei Zhang, Yujie Wei +5
Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data and constrained computation resou…
PersonalVideo: High ID-Fidelity Video Customization without Dynamic and Semantic Degradation
Hengjia Li, Haonan Qiu, Shiwei Zhang +6
The current text-to-video (T2V) generation has made significant progress in synthesizing realistic general videos, but it is still under-explored in identity-specific human video g…
DreamVideo-2: Zero-Shot Subject-Driven Video Customization with Precise Motion Control
Yujie Wei, Shiwei Zhang, Hangjie Yuan +9
Recent advances in customized video generation have enabled users to create videos tailored to both specific subjects and motion trajectories. However, existing methods often requi…
EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models
Rui Zhao, Hangjie Yuan, Yujie Wei +8
Recent advancements in generation models have showcased remarkable capabilities in generating fantastic content. However, most of them are trained on proprietary high-quality data,…
Animate-X: Universal Character Image Animation with Enhanced Motion Representation
Shuai Tan, Biao Gong, Xiang Wang +6
Character image animation, which generates high-quality videos from a reference image and target pose sequence, has seen significant progress in recent years. However, most existin…
Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM
Huaxin Zhang, Xiaohao Xu, Xiang Wang +6
Towards open-ended Video Anomaly Detection (VAD), existing methods often exhibit biased detection when faced with challenging or unseen events and lack interpretability. To address…
UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animation
Xiang Wang, Shiwei Zhang, Changxin Gao +5
Recent diffusion-based human image animation techniques have demonstrated impressive success in synthesizing videos that faithfully follow a given reference identity and a sequence…
GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection
Huaxin Zhang, Xiang Wang, Xiaohao Xu +6
In recent years, video anomaly detection has been extensively investigated in both unsupervised and weakly supervised settings to alleviate costly temporal labeling. Despite signif…
A Recipe for Scaling up Text-to-Video Generation with Text-free Videos
Xiang Wang, Shiwei Zhang, Hangjie Yuan +6
Diffusion-based text-to-video generation has witnessed impressive progress in the past year yet still falls behind text-to-image generation. One of the key reasons is the limited s…
InstructVideo: Instructing Video Diffusion Models with Human Feedback
Hangjie Yuan, Shiwei Zhang, Xiang Wang +7
Diffusion models have emerged as the de facto paradigm for video generation. However, their reliance on web-scale data of varied quality often yields results that are visually unap…
VideoLCM: Video Latent Consistency Model
Xiang Wang, Shiwei Zhang, Han Zhang +4
Consistency models have demonstrated powerful capability in efficient image generation and allowed synthesis within a few sampling steps, alleviating the high computational cost in…
Hierarchical Spatio-temporal Decoupling for Text-to-Video Generation
Zhiwu Qing, Shiwei Zhang, Jiayu Wang +5
Despite diffusion models having shown powerful abilities to generate photorealistic images, generating videos that are realistic and diverse still remains in its infancy. One of th…
DreamTalk: When Emotional Talking Head Generation Meets Diffusion Probabilistic Models
Yifeng Ma, Shiwei Zhang, Jiayu Wang +3
Emotional talking head generation has attracted growing attention. Previous methods, which are mainly GAN-based, still struggle to consistently produce satisfactory results across…
I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models
Shiwei Zhang, Jiayu Wang, Yingya Zhang +6
Video synthesis has recently made remarkable strides benefiting from the rapid development of diffusion models. However, it still encounters challenges in terms of semantic accurac…