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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

StreamAvatar: Streaming Diffusion Models for Real-Time Interactive Human Avatars

Zhiyao Sun, Ziqiao Peng, Yifeng Ma +8

Real-time, streaming interactive avatars represent a critical yet challenging goal in digital human research. Although diffusion-based human avatar generation methods achieve remar…