collaborators

21 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

DreamX-World 1.0: A General-Purpose Interactive World Model

DreamX Team, Yancheng Bai, Rui Chen +20

DreamX-World 1.0 is a general-purpose interactive text/image-to-video world model for controllable long-horizon generation. It supports camera navigation, revisits to previously ob…

cs.CV2026

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…

cs.CV2026

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…