5 papers
OpenT2M: No-frill Motion Generation with Open-source,Large-scale, High-quality Data
Bin Cao, Sipeng Zheng, Hao Luo +3
Text-to-motion (T2M) generation aims to create realistic human movements from text descriptions, with promising applications in animation and robotics. Despite recent progress, cur…
SAGE-Music: Low-Latency Symbolic Music Generation via Attribute-Specialized Key-Value Head Sharing
Jiaye Tan, Haonan Luo, Linfeng Song +10
Low-latency symbolic music generation is essential for real-time improvisation and human-AI co-creation. Existing transformer-based models, however, face a trade-off between infere…
Free-Form Motion Control: Controlling the 6D Poses of Camera and Objects in Video Generation
Xincheng Shuai, Henghui Ding, Zhenyuan Qin +3
Controlling the movements of dynamic objects and the camera within generated videos is a meaningful yet challenging task. Due to the lack of datasets with comprehensive 6D pose ann…
AnyI2V: Animating Any Conditional Image with Motion Control
Ziye Li, Hao Luo, Xincheng Shuai +1
Recent advancements in video generation, particularly in diffusion models, have driven notable progress in text-to-video (T2V) and image-to-video (I2V) synthesis. However, challeng…
Grid: Omni Visual Generation
Cong Wan, Xiangyang Luo, Hao Luo +7
Visual generation has witnessed remarkable progress in single-image tasks, yet extending these capabilities to temporal sequences remains challenging. Current approaches either bui…