9 citations · 11 across the 28 of their papers we have counts for
9 papers · 1 filter
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…
Aura: Consistent Multi-Subject Video Generation via VLM-Grounded Semantic Alignment
Zixiang Zhou, Zhentao Yu, Yifeng Ma +9
Subject-driven and multi-element video generation are central to controllable video synthesis, but existing methods still struggle to preserve identity consistency and model comple…
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…
HarmoView: Harmonizing Multi-View Constraints for Identity-Consistent Video Generation
Cong Wang, Zhentao Yu, Hongmei Wang +7
Current identity-consistent video generation methods struggle to preserve appearance fidelity under large viewpoint changes. While introducing multi-view reference input offers a n…
SARA: Semantically Adaptive Relational Alignment for Video Diffusion Models
Jiesong Lian, Zixiang Zhou, Ruizhe Zhong +6
Recent video diffusion models (VDMs) synthesize visually convincing clips, yet still drop entities, mis-bind attributes, and weaken the interactions specified in the prompt. Repres…
Implicit Preference Alignment for Human Image Animation
Yuanzhi Wang, Xuhua Ren, Jiaxiang Cheng +5
Human image animation has witnessed significant advancements, yet generating high-fidelity hand motions remains a persistent challenge due to their high degrees of freedom and moti…
Euphonium: Steering Video Flow Matching via Process Reward Gradient Guided Stochastic Dynamics
Ruizhe Zhong, Jiesong Lian, Xiaoyue Mi +4
While online Reinforcement Learning has emerged as a crucial technique for aligning flow matching models with human preferences, current approaches are hindered by inefficient expl…
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…