8 papers
FADE: From Passive Verification to Active Discovery in Counterfactual Video Understanding
Fufangchen Zhao, Jinhu Fu, Jiachen Lei +3
Counterfactual video understanding evaluates whether models grasp physical and commonsense regularities. However, existing multiple-choice question (MCQ) benchmarks inadvertently l…
Learning Explicit Physical Parameter Control and Benchmarking for Video Generation
Yanxun Li, Hao Wen, Bingze Song +7
Recent advances in image-to-video generation have improved visual realism, making physically grounded and controllable dynamics an important step toward future world simulation. Cu…
OmniDance: Multimodal Driven Dance Video Generation with Large-scale Internet Data
Kaixing Yang, Jiashu Zhu, Xulong Tang +8
Music-driven dance video generation aims to synthesize expressive human motion that is temporally aligned with music while maintaining high visual fidelity. Despite recent progress…
Embedding-perturbed Exploration Preference Optimization for Flow Models
Sujie Hu, Chubin Chen, Jiashu Zhu +3
Recent advancements have established Reinforcement Learning (RL) as a pivotal paradigm for aligning generative models with human intent. However, group-based optimization framework…
MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation
Kaixing Yang, Jiashu Zhu, Xulong Tang +7
With the rise of online dance-video platforms and rapid advances in AI-generated content (AIGC), music-driven dance generation has emerged as a compelling research direction. Despi…
Extending One-Step Image Generation from Class Labels to Text via Discriminative Text Representation
Chenxi Zhao, Chen Zhu, Xiaokun Feng +6
Few-step generation has been a long-standing goal, with recent one-step generation methods exemplified by MeanFlow achieving remarkable results. Existing research on MeanFlow prima…