72 citations · 384 across the 36 of their papers we have counts for
51 papers
Guided Motion Diffusion for Controllable Human Motion Synthesis
Korrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn +1
Denoising diffusion models have shown great promise in human motion synthesis conditioned on natural language descriptions. However, integrating spatial constraints, such as pre-de…
Synthesizing Diverse Human Motions in 3D Indoor Scenes
Kaifeng Zhao, Yan Zhang, Shaofei Wang +2
We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner. Existing approac…
Dynamic Point Fields
Sergey Prokudin, Qianli Ma, Maxime Raafat +2
Recent years have witnessed significant progress in the field of neural surface reconstruction. While the extensive focus was put on volumetric and implicit approaches, a number of…
Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric Views
Siwei Zhang, Qianli Ma, Yan Zhang +3
Automatic perception of human behaviors during social interactions is crucial for AR/VR applications, and an essential component is estimation of plausible 3D human pose and shape…
Factor Fields: A Unified Framework for Neural Fields and Beyond
Anpei Chen, Zexiang Xu, Xinyue Wei +3
We present Factor Fields, a novel framework for modeling and representing signals. Factor Fields decomposes a signal into a product of factors, each represented by a classical or n…
HARP: Personalized Hand Reconstruction from a Monocular RGB Video
Korrawe Karunratanakul, Sergey Prokudin, Otmar Hilliges +1
We present HARP (HAnd Reconstruction and Personalization), a personalized hand avatar creation approach that takes a short monocular RGB video of a human hand as input and reconstr…
3D Segmentation of Humans in Point Clouds with Synthetic Data
Ayça Takmaz, Jonas Schult, Irem Kaftan +5
Segmenting humans in 3D indoor scenes has become increasingly important with the rise of human-centered robotics and AR/VR applications. To this end, we propose the task of joint 3…
ARAH: Animatable Volume Rendering of Articulated Human SDFs
Shaofei Wang, Katja Schwarz, Andreas Geiger +1
Combining human body models with differentiable rendering has recently enabled animatable avatars of clothed humans from sparse sets of multi-view RGB videos. While state-of-the-ar…
Mask3D: Mask Transformer for 3D Semantic Instance Segmentation
Jonas Schult, Francis Engelmann, Alexander Hermans +3
Modern 3D semantic instance segmentation approaches predominantly rely on specialized voting mechanisms followed by carefully designed geometric clustering techniques. Building on…
Neural Point-based Shape Modeling of Humans in Challenging Clothing
Qianli Ma, Jinlong Yang, Michael J. Black +1
Parametric 3D body models like SMPL only represent minimally-clothed people and are hard to extend to clothing because they have a fixed mesh topology and resolution. To address th…
Compositional Human-Scene Interaction Synthesis with Semantic Control
Kaifeng Zhao, Shaofei Wang, Yan Zhang +2
Synthesizing natural interactions between virtual humans and their 3D environments is critical for numerous applications, such as computer games and AR/VR experiences. Our goal is…
Accurate 3D Body Shape Regression using Metric and Semantic Attributes
Vasileios Choutas, Lea Muller, Chun-Hao P. Huang +3
While methods that regress 3D human meshes from images have progressed rapidly, the estimated body shapes often do not capture the true human shape. This is problematic since, for…
KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints
Marko Mihajlovic, Aayush Bansal, Michael Zollhoefer +2
Image-based volumetric humans using pixel-aligned features promise generalization to unseen poses and identities. Prior work leverages global spatial encodings and multi-view geome…
Context-Aware Sequence Alignment using 4D Skeletal Augmentation
Taein Kwon, Bugra Tekin, Siyu Tang +1
Temporal alignment of fine-grained human actions in videos is important for numerous applications in computer vision, robotics, and mixed reality. State-of-the-art methods directly…
COAP: Compositional Articulated Occupancy of People
Marko Mihajlovic, Shunsuke Saito, Aayush Bansal +2
We present a novel neural implicit representation for articulated human bodies. Compared to explicit template meshes, neural implicit body representations provide an efficient mech…
Interactive Object Segmentation in 3D Point Clouds
Theodora Kontogianni, Ekin Celikkan, Siyu Tang +1
We propose an interactive approach for 3D instance segmentation, where users can iteratively collaborate with a deep learning model to segment objects in a 3D point cloud directly.…
Human-Aware Object Placement for Visual Environment Reconstruction
Hongwei Yi, Chun-Hao P. Huang, Dimitrios Tzionas +5
Humans are in constant contact with the world as they move through it and interact with it. This contact is a vital source of information for understanding 3D humans, 3D scenes, an…
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…
The Wanderings of Odysseus in 3D Scenes
Yan Zhang, Siyu Tang
Our goal is to populate digital environments, in which digital humans have diverse body shapes, move perpetually, and have plausible body-scene contact. The core challenge is to ge…
EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devices
Siwei Zhang, Qianli Ma, Yan Zhang +5
Understanding social interactions from egocentric views is crucial for many applications, ranging from assistive robotics to AR/VR. Key to reasoning about interactions is to unders…
The Power of Points for Modeling Humans in Clothing
Qianli Ma, Jinlong Yang, Siyu Tang +1
Currently it requires an artist to create 3D human avatars with realistic clothing that can move naturally. Despite progress on 3D scanning and modeling of human bodies, there is s…
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 Motion Priors for 4D Human Body Capture in 3D Scenes
Siwei Zhang, Yan Zhang, Federica Bogo +2
Recovering high-quality 3D human motion in complex scenes from monocular videos is important for many applications, ranging from AR/VR to robotics. However, capturing realistic hum…
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…