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Research Overview

Inferring and exploiting contact

Generative Proxemics: A Prior for 3D Social Interaction from Images

BITE -- Dog Shape and Pose from an Image

HOLD -- inferring 3D hand and object shape from video

MOVER -- Reconstructing 3D Scenes and People using Interaction

Datasets for understanding humans and animals

The Poses for Equine Research Dataset (PFERD)

BEAT2 Dataset for Holistic Co-Speech Gesture Generation

ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation

The BioAMASS Dataset

OpenCapBench dataset

Human health and the 3D body

Body Shape Models in Treating Anorexia Nervosa

Customized Bone Plants for Humerus Shaft Fractures

Reconstructing Signing Avatars From Video Using Linguistic Priors

The AI animator

HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles

Gaussian Garments

PuzzleAvatar: Assembling 3D Avatars from Personal Albums

FLARE: Fast Learning of Animatable and Relightable Mesh Avatars

Language, Vision, and World Models

AWOL: Analysis WithOut synthesis using Language

Re-Thinking Inverse Graphics with Large Language Models

TeCH: Text-guided Reconstruction of Clothed Humans

Human pose, shape, and motion capture

WHAM: Reconstructing World-grounded Humans with Accurate 3D Motion

3D Human Pose Estimation via Intuitive Physics

Accurate 3D Body Shape Regression using Metric and Semantic Attributes

BEV

Generating human motion

Generating Human Interaction Motions in Scenes with Text Control

TEMOS: Generating Diverse Human Motions from Text

EMAGE: Full-body Gestures from Audio

TEACH: Temporal Action Compositions for 3D Humans

Robot Perception Group

AirCap: 3D Motion Capture

AirCap: Perception-Based Control

Data Team

Lab Tours and Public Outreach

Collecting Data - From the Idea to the Publication

Capture Technologies Setup

Completed Projects

Clothing Capture and Modeling

Modeling Human Movement

/ps/projects/action-and-behavior

/ps/projects/inverse-graphics-proj

/ps/projects/image-segmentation-and-semantics

/ps/projects/groups-and-crowds

/ps/projects/learning-from-synthetic-data

/ps/projects/learning-high-dimensional-deep-representations

/ps/projects/efficient-and-scalable-inference

Hierarchical Graphs for Generalized Modelling of Clothing Dynamics

Learning to Resolve Intersections in Neural Multi-Garment Simulations

Reconstructing Simulation-Ready Clothing with Photo-Realistic Appearance from Multi-View Video

Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles

Human Hair Reconstruction with Strand-Aligned 3D Gaussians

Joker: Conditional 3D Head Synthesis with Extreme Facial Expressions

Goal Driven Motion Generation

Perzeptive Systeme

Semantic Scene Understanding

Photo: Wolfram Scheible.

Scene understanding, in contrast to object recognition, attempts to analyze objects in context with respect to the 3D structure of the scene, its layout, and the spatial, functional, and semantic relationships between objects. Our research in this area combines object detection/recognition with 3D reconstruction and spatial reasoning. We believe that the integrated analysis of low-level image features, together with high-level semantic and 3D object models, will enable robust scene understanding in complex and ambiguous environments and will provide the foundation for further reasoning.