23 citations · 36 across the 10 of their papers we have counts for
10 papers
Spatial-Temporal Multi-Scale Quantization for Flexible Motion Generation
Zan Wang, Jingze Zhang, Yixin Chen +3
Despite significant advancements in human motion generation, current motion representations, typically formulated as discrete frame sequences, still face two critical limitations:…
InteractAnything: Zero-shot Human Object Interaction Synthesis via LLM Feedback and Object Affordance Parsing
Jinlu Zhang, Yixin Chen, Zan Wang +3
Recent advances in 3D human-aware generation have made significant progress. However, existing methods still struggle with generating novel Human Object Interaction (HOI) from text…
PhysPart: Physically Plausible Part Completion for Interactable Objects
Rundong Luo, Haoran Geng, Congyue Deng +5
Interactable objects are ubiquitous in our daily lives. Recent advances in 3D generative models make it possible to automate the modeling of these objects, benefiting a range of ap…
R2G: Reasoning to Ground in 3D Scenes
Yixuan Li, Zan Wang, Wei Liang
We propose Reasoning to Ground (R2G), a neural symbolic model that grounds the target objects within 3D scenes in a reasoning manner. In contrast to prior works, R2G explicitly mod…
Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordance
Zan Wang, Yixin Chen, Baoxiong Jia +7
Despite significant advancements in text-to-motion synthesis, generating language-guided human motion within 3D environments poses substantial challenges. These challenges stem pri…
Scaling Up Dynamic Human-Scene Interaction Modeling
Nan Jiang, Zhiyuan Zhang, Hongjie Li +6
Confronting the challenges of data scarcity and advanced motion synthesis in human-scene interaction modeling, we introduce the TRUMANS dataset alongside a novel HSI motion synthes…
Diffusion-based Generation, Optimization, and Planning in 3D Scenes
Siyuan Huang, Zan Wang, Puhao Li +5
We introduce SceneDiffuser, a conditional generative model for 3D scene understanding. SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization…
Perceive, Ground, Reason, and Act: A Benchmark for General-purpose Visual Representation
Jiangyong Huang, William Yicheng Zhu, Baoxiong Jia +4
Current computer vision models, unlike the human visual system, cannot yet achieve general-purpose visual understanding. Existing efforts to create a general vision model are limit…
HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes
Zan Wang, Yixin Chen, Tengyu Liu +3
Learning to generate diverse scene-aware and goal-oriented human motions in 3D scenes remains challenging due to the mediocre characteristics of the existing datasets on Human-Scen…
PEARL: Parallelized Expert-Assisted Reinforcement Learning for Scene Rearrangement Planning
Hanqing Wang, Zan Wang, Wei Liang +1
Scene Rearrangement Planning (SRP) is an interior task proposed recently. The previous work defines the action space of this task with handcrafted coarse-grained actions that are i…