10 papers
Getting Space Right: Agentic Rewards for Image Generation
Xiaofeng Tan, Jiaxin Lin, Haobo Yuan +5
Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accurate rewards and effective onl…
SGF+: Decoupling Gradient Flows for Autoregressive Video Generation
Zihan Su, Junhao Zhuang, Yaowei Li +10
Autoregressive video generation requires denoising the current frames while writing their key-value representations as context for future predictions. However, these two roles typi…
Where and When to Force: Routed Forcing for Streaming Avatars
Zihan Su, Siwen Lu, Junhao Zhuang +6
Audio-driven streaming avatar generation requires real-time synthesis of speech-synchronized videos with dynamic and diverse motion. Self Forcing uses Distribution Matching Distill…
EchoWM: Open and Enterable Omnimodal World Models
Songchun Zhang, Yaowei Li, Junhao Zhuang +19
We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, environmental sound, music an…
Cycle-World: Mitigating Error Accumulation in Long-term Video World Models via Reverse-Prediction Cycle Consistency
Zihan Su, Teng Hu, Jiangning Zhang +4
Autoregressive diffusion models have enabled high-quality video generation, yet their sequential nature inherently suffers from error accumulation. In long-horizon video synthesis,…
Evolution of Video Generative Foundations
Teng Hu, Jiangning Zhang, Hongrui Huang +7
The rapid advancement of Artificial Intelligence Generated Content (AIGC) has revolutionized video generation, enabling systems ranging from proprietary pioneers like OpenAI's Sora…
PoseAnything: Universal Pose-guided Video Generation with Part-aware Temporal Coherence
Ruiyan Wang, Teng Hu, Kaihui Huang +3
Pose-guided video generation refers to controlling the motion of subjects in generated video through a sequence of poses. It enables precise control over subject motion and has imp…
Harmony: Harmonizing Audio and Video Generation through Cross-Task Synergy
Teng Hu, Zhentao Yu, Guozhen Zhang +6
The synthesis of synchronized audio-visual content is a key challenge in generative AI, with open-source models facing challenges in robust audio-video alignment. Our analysis reve…
UltraGen: High-Resolution Video Generation with Hierarchical Attention
Teng Hu, Jiangning Zhang, Zihan Su +1
Recent advances in video generation have made it possible to produce visually compelling videos, with wide-ranging applications in content creation, entertainment, and virtual real…
IAR2: Improving Autoregressive Visual Generation with Semantic-Detail Associated Token Prediction
Ran Yi, Teng Hu, Zihan Su +2
Autoregressive models have emerged as a powerful paradigm for visual content creation, but often overlook the intrinsic structural properties of visual data. Our prior work, IAR, i…