6 papers
Exploring the Role of Synthetic Data Augmentation in Controllable Human-Centric Video Generation
Yuanchen Fei, Yude Zou, Zejian Kang +3
Controllable human video generation aims to produce realistic videos of humans with explicitly guided motions and appearances,serving as a foundation for digital humans, animation,…
DataCube: A Video Retrieval Platform via Natural Language Semantic Profiling
Yiming Ju, Hanyu Zhao, Quanyue Ma +5
Large-scale video repositories are increasingly available for modern video understanding and generation tasks. However, transforming raw videos into high-quality, task-specific dat…
EventFlash: Towards Efficient MLLMs for Event-Based Vision
Shaoyu Liu, Jianing Li, Guanghui Zhao +4
Event-based multimodal large language models (MLLMs) enable robust perception in high-speed and low-light scenarios, addressing key limitations of frame-based MLLMs. However, curre…
LoL: Longer than Longer, Scaling Video Generation to Hour
Justin Cui, Jie Wu, Ming Li +6
Recent research in long-form video generation has shifted from bidirectional to autoregressive models, yet these methods commonly suffer from error accumulation and a loss of long-…
Self-Forcing++: Towards Minute-Scale High-Quality Video Generation
Justin Cui, Jie Wu, Ming Li +6
Diffusion models have revolutionized image and video generation, achieving unprecedented visual quality. However, their reliance on transformer architectures incurs prohibitively h…
RewardDance: Reward Scaling in Visual Generation
Jie Wu, Yu Gao, Zilyu Ye +9
Reward Models (RMs) are critical for improving generation models via Reinforcement Learning (RL), yet the RM scaling paradigm in visual generation remains largely unexplored. It pr…