20 citations · 21 across the 11 of their papers we have counts for
12 papers
HounsWorld: A Multimodal World Model for Hidden Patient-State Readout, Reconstruction, and Simulation
Yunhao Bai, Zhongwei Qiu, Guangyu Guo +5
Clinical intelligence requires estimating a patient's underlying condition from incomplete observations rather than learning isolated mappings from scans to answers. Volumetric med…
Scene and Human in One World: Reconstruction in a Feedforward Pass
Boao Shi, Qiao Feng, Yiming Huang +1
Reconstructing humans in dynamic scenes from moving monocular cameras remains challenging due to scale ambiguity, human-scene misalignment, and occlusion interference. Rather than…
Text2Interact: High-Fidelity and Diverse Text-to-Two-Person Interaction Generation
Qingxuan Wu, Zhiyang Dou, Chuan Guo +5
Modeling human-human interactions from text remains challenging because it requires not only realistic individual dynamics but also precise, text-consistent spatiotemporal coupling…
PhysHMR: Learning Humanoid Control Policies from Vision for Physically Plausible Human Motion Reconstruction
Qiao Feng, Yiming Huang, Yufu Wang +2
Reconstructing physically plausible human motion from monocular videos remains a challenging problem in computer vision and graphics. Existing methods primarily focus on kinematics…
PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation
Chen Wang, Chuhao Chen, Yiming Huang +4
Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limit…
FormCoach: Lift Smarter, Not Harder
Xiaoye Zuo, Nikos Athanasiou, Ginger Delmas +3
Good form is the difference between strength and strain, yet for the fast-growing community of at-home fitness enthusiasts, expert feedback is often out of reach. FormCoach transfo…
Vid2Sim: Generalizable, Video-based Reconstruction of Appearance, Geometry and Physics for Mesh-free Simulation
Chuhao Chen, Zhiyang Dou, Chen Wang +5
Faithfully reconstructing textured shapes and physical properties from videos presents an intriguing yet challenging problem. Significant efforts have been dedicated to advancing s…
ModSkill: Physical Character Skill Modularization
Yiming Huang, Zhiyang Dou, Lingjie Liu
Human motion is highly diverse and dynamic, posing challenges for imitation learning algorithms that aim to generalize motor skills for controlling simulated characters. Previous m…
CoMo: Controllable Motion Generation through Language Guided Pose Code Editing
Yiming Huang, Weilin Wan, Yue Yang +3
Text-to-motion models excel at efficient human motion generation, but existing approaches lack fine-grained controllability over the generation process. Consequently, modifying sub…
DiffusionPhase: Motion Diffusion in Frequency Domain
Weilin Wan, Yiming Huang, Shutong Wu +4
In this study, we introduce a learning-based method for generating high-quality human motion sequences from text descriptions (e.g., ``A person walks forward"). Existing techniques…
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…
Generic Attention-model Explainability by Weighted Relevance Accumulation
Yiming Huang, Aozhe Jia, Xiaodan Zhang +1
Attention-based transformer models have achieved remarkable progress in multi-modal tasks, such as visual question answering. The explainability of attention-based methods has rece…