13 papers
TRACE: Typed Reference-Aware Conversational Editing for Humanoid Motion Diffusion
Zejian Kang, Yifu Luo, Boyang Shen +9
Language-conditioned humanoid motion generation enables users to create and refine robot movements through natural language. The central challenge is to connect an underspecified r…
Unravel: Recovering an Interactive 3D Scene from a Single Image
Hui Shan, Keyang Luo, Binjia Zhou +10
We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable asset. Existing generators ei…
Awomo-SimDataEngine: Agentic Simulation-ReadyWorld Generation
PhysicalRSI Team, Danjiao Ma, Enhui Ma +21
Generating useful robot-training data requires more than visually plausiblescenes: objects must support interaction, placements must remain physicallyvalid, and tasks must admit re…
GIFT: Geometry-Invariant Fine-Tuning for Non-Lambertian Monocular Depth Estimation
Xianghui Fan, Zhaoyu Chen, Bingqian Wu +6
Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often hallucinate depth on non-Lamber…
Teleopit: A Full-Embodiment Humanoid Teleoperation System
Bingqian Wu, Zicheng Xu, Xianghui Fan +2
Humanoid teleoperation for demonstration collection requires coordinated whole-body motion, continuous dexterous hand control, and viewpoint control. Existing systems either simpli…
fMRI2Face: A Full-HD fMRI-Video Dataset and Geometry-Guided Neural Decoding Framework for Dynamic Human Face Reconstruction
Jingyang Huo, Xiangru Huang, Chentao Shen +6
Reconstructing dynamic human faces from brain activity provides a powerful way to study how the mind perceives identity, expression, and facial motion. However, progress in fMRI-ba…
AudioFace: Language-Assisted Speech-Driven Facial Animation with Multimodal Language Models
Kai Zheng, Zejian Kang, Rui Mao +4
Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth movements. However, directly m…
SuperFace: Preference-Aligned Facial Expression Estimation Beyond Pseudo Supervision
Zejian Kang, Xuanyang Xu, Wentao Yang +6
Accurate facial estimation is crucial for realistic digital human animation, and ARKit blendshape coefficients offer an interpretable representation by mapping facial motions to se…
Exploring the Role of Synthetic Data Augmentation in Controllable Human-Centric Video Generation
Yuanchen Fei, Yude Zou, Zejian Kang +3
Controllable human video generation aims to produce realistic videos of humans with explicitly guided motions and appearances,serving as a foundation for digital humans, animation,…
SparseOIT: Improving Order-Independent Transparency 3DGS via Active Set Method
Wentao Yang, Fanzhen Kong, Zejian Kang +1
3D Gaussian Splatting (3DGS) has received tremendous popularity over the past few years due to its photorealistic visual appearance. However, 3DGS uses volumetric rendering that is…
SemanticFace: Semantic Facial Action Estimation via Semantic Distillation in Interpretable Space
Zejian Kang, Kai Zheng, Yuanchen Fei +3
Facial action estimation from a single image is often formulated as predicting or fitting parameters in compact expression spaces, which lack explicit semantic interpretability. Ho…
Auto3R: Automated 3D Reconstruction and Scanning via Data-driven Uncertainty Quantification
Chentao Shen, Sizhe Zheng, Bingqian Wu +5
Traditional high-quality 3D scanning and reconstruction typically relies on human labor to plan the scanning procedure. With the rapid development of embodied systems such as drone…
KeyframeFace: Language-Driven Facial Animation via Semantic Keyframes
Jingchao Wu, Zejian Kang, Haibo Liu +2
Facial animation is a core component for creating digital characters in Computer Graphics (CG) industry. A typical production workflow relies on sparse, semantically meaningful key…