1 citations · 4 across the 22 of their papers we have counts for
25 papers
FilmWeaver: Weaving Consistent Multi-Shot Videos with Cache-Guided Autoregressive Diffusion
Xiangyang Luo, Qingyu Li, Xiaokun Liu +7
Current video generation models perform well at single-shot synthesis but struggle with multi-shot videos, facing critical challenges in maintaining character and background consis…
PatchVSR: Breaking Video Diffusion Resolution Limits with Patch-wise Video Super-Resolution
Shian Du, Menghan Xia, Chang Liu +5
Pre-trained video generation models hold great potential for generative video super-resolution (VSR). However, adapting them for full-size VSR, as most existing methods do, suffers…
FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generation
Kaiyi Huang, Yukun Huang, Xintao Wang +6
AI-driven content creation has shown potential in film production. However, existing film generation systems struggle to implement cinematic principles and thus fail to generate pr…
FullDiT2: Efficient In-Context Conditioning for Video Diffusion Transformers
Xuanhua He, Quande Liu, Zixuan Ye +7
Fine-grained and efficient controllability on video diffusion transformers has raised increasing desires for the applicability. Recently, In-context Conditioning emerged as a power…
UNIC: Unified In-Context Video Editing
Zixuan Ye, Xuanhua He, Quande Liu +7
Recent advances in text-to-video generation have sparked interest in generative video editing tasks. Previous methods often rely on task-specific architectures (e.g., additional ad…
CamCloneMaster: Enabling Reference-based Camera Control for Video Generation
Yawen Luo, Jianhong Bai, Xiaoyu Shi +6
Camera control is crucial for generating expressive and cinematic videos. Existing methods rely on explicit sequences of camera parameters as control conditions, which can be cumbe…
Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval
Jiwen Yu, Jianhong Bai, Yiran Qin +5
Recent advances in interactive video generation have shown promising results, yet existing approaches struggle with scene-consistent memory capabilities in long video generation du…
Learning Video Generation for Robotic Manipulation with Collaborative Trajectory Control
Xiao Fu, Xintao Wang, Xian Liu +5
Recent advances in video diffusion models shows promise for generating robotic decision-making data, with trajectory conditions further enabling fine-grained control. However, exis…
Scaling Image and Video Generation via Test-Time Evolutionary Search
Haoran He, Jiajun Liang, Xintao Wang +4
As the marginal cost of scaling computation (data and parameters) during model pre-training continues to increase substantially, test-time scaling (TTS) has emerged as a promising…
Flow-GRPO: Training Flow Matching Models via Online RL
Jie Liu, Gongye Liu, Jiajun Liang +6
We propose Flow-GRPO, the first method to integrate online policy gradient reinforcement learning (RL) into flow matching models. Our approach uses two key strategies: (1) an ODE-t…
A Survey of Interactive Generative Video
Jiwen Yu, Yiran Qin, Haoxuan Che +7
Interactive Generative Video (IGV) has emerged as a crucial technology in response to the growing demand for high-quality, interactive video content across various domains. In this…
FullDiT: Multi-Task Video Generative Foundation Model with Full Attention
Xuan Ju, Weicai Ye, Quande Liu +6
Current video generative foundation models primarily focus on text-to-video tasks, providing limited control for fine-grained video content creation. Although adapter-based approac…
DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers
Minglei Shi, Ziyang Yuan, Haotian Yang +10
Diffusion models have demonstrated remarkable success in various image generation tasks, but their performance is often limited by the uniform processing of inputs across varying c…
Any2Caption:Interpreting Any Condition to Caption for Controllable Video Generation
Shengqiong Wu, Weicai Ye, Jiahao Wang +8
To address the bottleneck of accurate user intent interpretation within the current video generation community, we present Any2Caption, a novel framework for controllable video gen…
Position: Interactive Generative Video as Next-Generation Game Engine
Jiwen Yu, Yiran Qin, Haoxuan Che +5
Modern game development faces significant challenges in creativity and cost due to predetermined content in traditional game engines. Recent breakthroughs in video generation model…
ReCamMaster: Camera-Controlled Generative Rendering from A Single Video
Jianhong Bai, Menghan Xia, Xiao Fu +8
Camera control has been actively studied in text or image conditioned video generation tasks. However, altering camera trajectories of a given video remains under-explored, despite…
CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation
Qinghe Wang, Yawen Luo, Xiaoyu Shi +7
In this work, we present CineMaster, a novel framework for 3D-aware and controllable text-to-video generation. Our goal is to empower users with comparable controllability as profe…
FlexDuo: A Pluggable System for Enabling Full-Duplex Capabilities in Speech Dialogue Systems
Borui Liao, Yulong Xu, Jiao Ou +4
Full-Duplex Speech Dialogue Systems (Full-Duplex SDS) have significantly enhanced the naturalness of human-machine interaction by enabling real-time bidirectional communication. Ho…
Improving Video Generation with Human Feedback
Jie Liu, Gongye Liu, Jiajun Liang +14
Video generation has achieved significant advances through rectified flow techniques, but issues like unsmooth motion and misalignment between videos and prompts persist. In this w…
GameFactory: Creating New Games with Generative Interactive Videos
Jiwen Yu, Yiran Qin, Xintao Wang +3
Generative videos have the potential to revolutionize game development by autonomously creating new content. In this paper, we present GameFactory, a framework for action-controlle…
ConceptMaster: Multi-Concept Video Customization on Diffusion Transformer Models Without Test-Time Tuning
Yuzhou Huang, Ziyang Yuan, Quande Liu +6
Text-to-video generation has made remarkable advancements through diffusion models. However, Multi-Concept Video Customization (MCVC) remains a significant challenge. We identify t…
SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints
Jianhong Bai, Menghan Xia, Xintao Wang +6
Recent advancements in video diffusion models have shown exceptional abilities in simulating real-world dynamics and maintaining 3D consistency. This progress inspires us to invest…
StyleMaster: Stylize Your Video with Artistic Generation and Translation
Zixuan Ye, Huijuan Huang, Xintao Wang +3
Style control has been popular in video generation models. Existing methods often generate videos far from the given style, cause content leakage, and struggle to transfer one vide…
3DTrajMaster: Mastering 3D Trajectory for Multi-Entity Motion in Video Generation
Xiao Fu, Xian Liu, Xintao Wang +7
This paper aims to manipulate multi-entity 3D motions in video generation. Previous methods on controllable video generation primarily leverage 2D control signals to manipulate obj…