9 papers
CoT-Edit: Let CoT Guide Instruction Video Editing
Sen Liang, Fengbin Guan, Youliang Zhang +2
Text-driven instruction-based video editing in complex scenes remains challenging: purely textual prompts often fail to capture precise spatial relationships and physical constrain…
AgentHOI: Multi-Agent Reasoning for Human-Object-Interaction Video Generation via Implicit Representation Alignment
Ziyao Huang, Shunkai Li, Juan Cao +7
Recent advances in video diffusion models have spurred interest in human-object interaction (HOI) video generation, which demands fine-grained control over interaction logic beyond…
Goku: A Million-Scale Universal Dataset and Benchmark for Instruction-Based Video Editing
Sen Liang, Cong Wang, Zhentao Yu +8
Existing instruction-based video editing datasets commonly focus on single-task appearance editing, failing to meet the complex creative demands of real-world scenarios. To bridge…
OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration
Xinchen Zhang, Bowei Liu, Jiale Liu +7
Visual outcomes are increasingly central to multimodal large language models, making reliable and fine-grained verification essential for scaling generalist foundation models. In t…
Making Avatars Interact: Towards Text-Driven Human-Object Interaction for Controllable Talking Avatars
Youliang Zhang, Zhengguang Zhou, Zhentao Yu +11
Generating talking avatars is a fundamental task in video generation. Although existing methods can generate full-body talking avatars with simple human motion, extending this task…
ActAvatar: Temporally-Aware Precise Action Control for Talking Avatars
Ziqiao Peng, Yi Chen, Yifeng Ma +10
Despite significant advances in talking avatar generation, existing methods face critical challenges: insufficient text-following capability for diverse actions, lack of temporal a…