88 citations · 423 across the 74 of their papers we have counts for
15 papers · 1 filter
SAGA: Stochastic Whole-Body Grasping with Contact
Yan Wu, Jiahao Wang, Yan Zhang +4
The synthesis of human grasping has numerous applications including AR/VR, video games and robotics. While methods have been proposed to generate realistic hand-object interaction…
I M Avatar: Implicit Morphable Head Avatars from Videos
Yufeng Zheng, Victoria Fernández Abrevaya, Marcel C. Bühler +3
Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details. Neural volumetric representati…
D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactions
Sammy Christen, Muhammed Kocabas, Emre Aksan +3
We introduce the dynamic grasp synthesis task: given an object with a known 6D pose and a grasp reference, our goal is to generate motions that move the object to a target 6D pose.…
Human Performance Capture from Monocular Video in the Wild
Chen Guo, Xu Chen, Jie Song +1
Capturing the dynamically deforming 3D shape of clothed human is essential for numerous applications, including VR/AR, autonomous driving, and human-computer interaction. Existing…
Render In-between: Motion Guided Video Synthesis for Action Interpolation
Hsuan-I Ho, Xu Chen, Jie Song +1
Upsampling videos of human activity is an interesting yet challenging task with many potential applications ranging from gaming to entertainment and sports broadcasting. The main d…
Shape-aware Multi-Person Pose Estimation from Multi-View Images
Zijian Dong, Jie Song, Xu Chen +2
In this paper we contribute a simple yet effective approach for estimating 3D poses of multiple people from multi-view images. Our proposed coarse-to-fine pipeline first aggregates…
SPEC: Seeing People in the Wild with an Estimated Camera
Muhammed Kocabas, Chun-Hao P. Huang, Joachim Tesch +3
Due to the lack of camera parameter information for in-the-wild images, existing 3D human pose and shape (HPS) estimation methods make several simplifying assumptions: weak-perspec…
A Skeleton-Driven Neural Occupancy Representation for Articulated Hands
Korrawe Karunratanakul, Adrian Spurr, Zicong Fan +2
We present Hand ArticuLated Occupancy (HALO), a novel representation of articulated hands that bridges the advantages of 3D keypoints and neural implicit surfaces and can be used i…
Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentation
Zicong Fan, Adrian Spurr, Muhammed Kocabas +3
In natural conversation and interaction, our hands often overlap or are in contact with each other. Due to the homogeneous appearance of hands, this makes estimating the 3D pose of…
Adversarial Motion Modelling helps Semi-supervised Hand Pose Estimation
Adrian Spurr, Pavlo Molchanov, Umar Iqbal +2
Hand pose estimation is difficult due to different environmental conditions, object- and self-occlusion as well as diversity in hand shape and appearance. Exhaustively covering thi…
PeCLR: Self-Supervised 3D Hand Pose Estimation from monocular RGB via Equivariant Contrastive Learning
Adrian Spurr, Aneesh Dahiya, Xi Wang +2
Encouraged by the success of contrastive learning on image classification tasks, we propose a new self-supervised method for the structured regression task of 3D hand pose estimati…
PARE: Part Attention Regressor for 3D Human Body Estimation
Muhammed Kocabas, Chun-Hao P. Huang, Otmar Hilliges +1
Despite significant progress, we show that state of the art 3D human pose and shape estimation methods remain sensitive to partial occlusion and can produce dramatically wrong pred…
SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes
Xu Chen, Yufeng Zheng, Michael J. Black +2
Neural implicit surface representations have emerged as a promising paradigm to capture 3D shapes in a continuous and resolution-independent manner. However, adapting them to artic…
Improved Learning of Robot Manipulation Tasks via Tactile Intrinsic Motivation
Nikola Vulin, Sammy Christen, Stefan Stevsic +1
In this paper we address the challenge of exploration in deep reinforcement learning for robotic manipulation tasks. In sparse goal settings, an agent does not receive any positive…
Spatial Attention Improves Iterative 6D Object Pose Estimation
Stefan Stevsic, Otmar Hilliges
The task of estimating the 6D pose of an object from RGB images can be broken down into two main steps: an initial pose estimation step, followed by a refinement procedure to corre…