4 citations · 10 across the 9 of their papers we have counts for
10 papers
EgoHand: Monocular 3D Hand Reconstruction from Egocentric Video
Chao-Yeh Chen, Tiffany Chen, Lin Duan +12
We introduce EgoHand, a monocular 3D hand reconstruction model that achieves state-of-the-art performance on egocentric video. Central to our approach is the curation of a high-qua…
GRAIL: Generating Humanoid Loco-Manipulation from World Models
Tianyi Xie, Haotian Zhang, Jinhyung Park +17
Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleoperation and motion capture a…
SOMA: Unifying Parametric Human Body Models
Jun Saito, Jiefeng Li, Michael de Ruyter +12
Parametric human body models are foundational to human reconstruction, animation, and simulation, yet they remain mutually incompatible: SMPL, SMPL-X, MHR, Anny, and related models…
Kimodo: Scaling Controllable Human Motion Generation
Davis Rempe, Mathis Petrovich, Ye Yuan +21
High-quality human motion data is becoming increasingly important for applications in robotics, simulation, and entertainment. Recent generative models offer a potential data sourc…
CARI4D: Category Agnostic 4D Reconstruction of Human-Object Interaction
Xianghui Xie, Bowen Wen, Yan Chang +5
Accurate capture of human-object interaction from ubiquitous sensors like RGB cameras is important for applications in human understanding, gaming, and robot learning. However, inf…
SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control
Zhengyi Luo, Ye Yuan, Tingwu Wang +25
Despite the rise of billion-parameter foundation models trained across thousands of graphical processing units (GPUs), similar scaling gains have not been shown for humanoid contro…
BLADE: Single-view Body Mesh Learning through Accurate Depth Estimation
Shengze Wang, Jiefeng Li, Tianye Li +5
Single-image human mesh recovery is a challenging task due to the ill-posed nature of simultaneous body shape, pose, and camera estimation. Existing estimators work well on images…
Denoising Vision Transformers
Jiawei Yang, Katie Z Luo, Jiefeng Li +6
We study a crucial yet often overlooked issue inherent to Vision Transformers (ViTs): feature maps of these models exhibit grid-like artifacts, which hurt the performance of ViTs i…
SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
Ailing Zeng, Lei Yang, Xuan Ju +3
When analyzing human motion videos, the output jitters from existing pose estimators are highly-unbalanced with varied estimation errors across frames. Most frames in a video are r…
ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis
Kailin Li, Lixin Yang, Xinyu Zhan +4
Estimating the articulated 3D hand-object pose from a single RGB image is a highly ambiguous and challenging problem, requiring large-scale datasets that contain diverse hand poses…