88 citations · 161 across the 15 of their papers we have counts for
19 papers
EgoHTR: Egocentric 4D Demonstrations of Human Terrain Traversal
Alex Brandes, Haig Conti Georges Sajelian, Manthan Patel +11
Deploying humanoid robots in unstructured terrain remains an open problem. While classic reinforcement learning struggles with the sheer complexity of real-world interactions, more…
CoMind: Understanding Collaborative Human Activity from Multiple Minds and Views
Alexey Gavryushin, Dingxi Zhang, Zhao Huang +8
Human-human collaboration is a fundamental aspect of everyday life, essential to success in a wide range of goal-directed activities from household tasks to professional teamwork.…
RHINO: Reconstructing Human Interactions with Novel Objects from Monocular Videos
Lixin Xue, Chengwei Zheng, Georgios Paschalidis +4
Reconstructing people, objects, and their interactions in 3D is a long-standing goal for intelligent systems. Often the input is RGB video from a moving camera, making the task ill…
Gaussian Wardrobe: Compositional 3D Gaussian Avatars for Free-Form Virtual Try-On
Zhiyi Chen, Hsuan-I Ho, Tianjian Jiang +3
We introduce Gaussian Wardrobe, a novel framework to digitalize compositional 3D neural avatars from multi-view videos. Existing methods for 3D neural avatars typically treat the h…
PHD: Personalized 3D Human Body Fitting with Point Diffusion
Hsuan-I Ho, Chen Guo, Po-Chen Wu +6
We introduce PHD, a novel approach for personalized 3D human mesh recovery (HMR) and body fitting that leverages user-specific shape information to improve pose estimation accuracy…
ODHSR: Online Dense 3D Reconstruction of Humans and Scenes from Monocular Videos
Zetong Zhang, Manuel Kaufmann, Lixin Xue +2
Creating a photorealistic scene and human reconstruction from a single monocular in-the-wild video figures prominently in the perception of a human-centric 3D world. Recent neural…
WorldPose: A World Cup Dataset for Global 3D Human Pose Estimation
Tianjian Jiang, Johsan Billingham, Sebastian Müksch +7
We present WorldPose, a novel dataset for advancing research in multi-person global pose estimation in the wild, featuring footage from the 2022 FIFA World Cup. While previous data…
ReLoo: Reconstructing Humans Dressed in Loose Garments from Monocular Video in the Wild
Chen Guo, Tianjian Jiang, Manuel Kaufmann +4
While previous years have seen great progress in the 3D reconstruction of humans from monocular videos, few of the state-of-the-art methods are able to handle loose garments that e…
EgoHDM: An Online Egocentric-Inertial Human Motion Capture, Localization, and Dense Mapping System
Bonan Liu, Handi Yin, Manuel Kaufmann +4
We present EgoHDM, an online egocentric-inertial human motion capture (mocap), localization, and dense mapping system. Our system uses 6 inertial measurement units (IMUs) and a com…
MultiPly: Reconstruction of Multiple People from Monocular Video in the Wild
Zeren Jiang, Chen Guo, Manuel Kaufmann +4
We present MultiPly, a novel framework to reconstruct multiple people in 3D from monocular in-the-wild videos. Reconstructing multiple individuals moving and interacting naturally…
EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild
Manuel Kaufmann, Jie Song, Chen Guo +5
We present EMDB, the Electromagnetic Database of Global 3D Human Pose and Shape in the Wild. EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters wi…
An Interpretable and Attention-based Method for Gaze Estimation Using Electroencephalography
Nina Weng, Martyna Plomecka, Manuel Kaufmann +3
Eye movements can reveal valuable insights into various aspects of human mental processes, physical well-being, and actions. Recently, several datasets have been made available tha…
Hi4D: 4D Instance Segmentation of Close Human Interaction
Yifei Yin, Chen Guo, Manuel Kaufmann +3
We propose Hi4D, a method and dataset for the automatic analysis of physically close human-human interaction under prolonged contact. Robustly disentangling several in-contact subj…
X-Avatar: Expressive Human Avatars
Kaiyue Shen, Chen Guo, Manuel Kaufmann +4
We present X-Avatar, a novel avatar model that captures the full expressiveness of digital humans to bring about life-like experiences in telepresence, AR/VR and beyond. Our method…
ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation
Zicong Fan, Omid Taheri, Dimitrios Tzionas +4
Humans intuitively understand that inanimate objects do not move by themselves, but that state changes are typically caused by human manipulation (e.g., the opening of a book). Thi…
Convolutional Autoencoders for Human Motion Infilling
Manuel Kaufmann, Emre Aksan, Jie Song +3
In this paper we propose a convolutional autoencoder to address the problem of motion infilling for 3D human motion data. Given a start and end sequence, motion infilling aims to c…
A Spatio-temporal Transformer for 3D Human Motion Prediction
Emre Aksan, Manuel Kaufmann, Peng Cao +1
We propose a novel Transformer-based architecture for the task of generative modelling of 3D human motion. Previous work commonly relies on RNN-based models considering shorter for…
Structured Prediction Helps 3D Human Motion Modelling
Emre Aksan, Manuel Kaufmann, Otmar Hilliges
Human motion prediction is a challenging and important task in many computer vision application domains. Existing work only implicitly models the spatial structure of the human ske…
Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time
Yinghao Huang, Manuel Kaufmann, Emre Aksan +3
We demonstrate a novel deep neural network capable of reconstructing human full body pose in real-time from 6 Inertial Measurement Units (IMUs) worn on the user's body. In doing so…