Gerard Pons-Moll

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Max Planck Society

Gerard Pons-Moll is the head of the Emmy Noether independent research group "Real Virtual Humans", senior researcher at the Max Planck for Informatics (MPII) in Saarbrücken, Germany, and Junior Faculty at Saarland Informatics Campus. His research lies at the intersection of computer vision, computer graphics and machine learning -- with special focus on analyzing people in videos, and creating virtual human models by "looking" at real ones. His research has produced some of the most advanced statistical human body models of pose, shape, soft-tissue and clothing (which are currently used for a number of applications in industry and research), as well as algorithms to track and reconstruct 3D people models from images, video, depth, and IMUs.

His work has received several awards including the prestigious Emmy Noether Grant (2018), a Google Faculty Research Award (2019), a Facebook Reality Labs Faculty Award (2018), and recently the German Pattern Recognition Award (2019), which is given annually by the German Pattern Recognition Society to one outstanding researcher in the fields of Computer Vision and Machine Learning. His work got Best Papers Awards at BMVC’13, Eurographics’17 and 3DV’18 and has been published at the top venues and journals including CVPR, ICCV, Siggraph, Eurographics, 3DV, IJCV and PAMI. He served as Area Chair for ECCV'18, 3DV'19, SCA'18'19, FG'20. He will serve as Area Chair for ECCV'20.

Featured Co-authors

Chao Zhang
103 publications
Bernt Schiele
102 publications
Hao Li
101 publications
Christian Theobalt
99 publications
Pascal Fua
93 publications
Mario Fritz
88 publications
Xiaoming Liu
50 publications
Michael J. Black
46 publications
Otmar Hilliges
41 publications
Bodo Rosenhahn
38 publications
Hans-Peter Seidel
38 publications

D-NeRF: Neural Radiance Fields for Dynamic Scenes

Neural rendering techniques combining machine learning with geometric re...
11/27/2020 ∙ by Albert Pumarola, et al. ∙ 8 ∙ share

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SelfPose: 3D Egocentric Pose Estimation from a Headset Mounted Camera

We present a solution to egocentric 3D body pose estimation from monocul...
11/02/2020 ∙ by Denis Tome, et al. ∙ 0 ∙ share

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Neural Unsigned Distance Fields for Implicit Function Learning

In this work we target a learnable output representation that allows con...
10/26/2020 ∙ by Julian Chibane, et al. ∙ 0 ∙ share

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SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results

The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020,...
10/26/2020 ∙ by Alexandre Saint, et al. ∙ 0 ∙ share

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LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration

We address the problem of fitting 3D human models to 3D scans of dressed...
10/23/2020 ∙ by Bharat Lal Bhatnagar, et al. ∙ 0 ∙ share

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Implicit Feature Networks for Texture Completion from Partial 3D Data

Prior work to infer 3D texture use either texture atlases, which require...
09/20/2020 ∙ by Julian Chibane, et al. ∙ 6 ∙ share

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SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing

While models of 3D clothing learned from real data exist, no method can ...
07/22/2020 ∙ by Garvita Tiwari, et al. ∙ 63 ∙ share

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Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction

Implicit functions represented as deep learning approximations are power...
07/22/2020 ∙ by Bharat Lal Bhatnagar, et al. ∙ 14 ∙ share

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Unsupervised Shape and Pose Disentanglement for 3D Meshes

Parametric models of humans, faces, hands and animals have been widely u...
07/22/2020 ∙ by Keyang Zhou, et al. ∙ 5 ∙ share

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Kinematic 3D Object Detection in Monocular Video

Perceiving the physical world in 3D is fundamental for self-driving appl...
07/19/2020 ∙ by Garrick Brazil, et al. ∙ 2 ∙ share

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DeepCap: Monocular Human Performance Capture Using Weak Supervision

Human performance capture is a highly important computer vision problem ...
03/18/2020 ∙ by Marc Habermann, et al. ∙ 1 ∙ share

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TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style

In this paper, we present TailorNet, a neural model which predicts cloth...
03/10/2020 ∙ by Chaitanya Patel, et al. ∙ 0 ∙ share

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The Virtual Tailor: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style

In this paper, we present TailorNet, a neural model which predicts cloth...
03/10/2020 ∙ by Chaitanya Patel, et al. ∙ 0 ∙ share

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Learning to Transfer Texture from Clothing Images to 3D Humans

In this paper, we present a simple yet effective method to automatically...
03/04/2020 ∙ by Aymen Mir, et al. ∙ 0 ∙ share

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Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion

While many works focus on 3D reconstruction from images, in this paper, ...
03/03/2020 ∙ by Julian Chibane, et al. ∙ 0 ∙ share

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360-Degree Textures of People in Clothing from a Single Image

In this paper we predict a full 3D avatar of a person from a single imag...
08/20/2019 ∙ by Verica Lazova, et al. ∙ 27 ∙ share

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Multi-Garment Net: Learning to Dress 3D People from Images

We present Multi-Garment Network (MGN), a method to predict body shape a...
08/19/2019 ∙ by Bharat Lal Bhatnagar, et al. ∙ 37 ∙ share

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Learning to Dress 3D People in Generative Clothing

Three-dimensional human body models are widely used in the analysis of h...
07/31/2019 ∙ by Qianli Ma, et al. ∙ 0 ∙ share

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Dressing 3D Humans using a Conditional Mesh-VAE-GAN

Three-dimensional human body models are widely used in the analysis of h...
07/31/2019 ∙ by Qianli Ma, et al. ∙ 0 ∙ share

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XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera

We present a real-time approach for multi-person 3D motion capture at ov...
07/01/2019 ∙ by Dushyant Mehta, et al. ∙ 13 ∙ share

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Shape Evasion: Preventing Body Shape Inference of Multi-Stage Approaches

Modern approaches to pose and body shape estimation have recently achiev...
05/27/2019 ∙ by Hosnieh Sattar, et al. ∙ 0 ∙ share

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Tex2Shape: Detailed Full Human Body Geometry from a Single Image

We present a simple yet effective method to infer detailed full human bo...
04/18/2019 ∙ by Thiemo Alldieck, et al. ∙ 16 ∙ share

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In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations

Convolutional Neural Network based approaches for monocular 3D human pos...
04/05/2019 ∙ by Ikhsanul Habibie, et al. ∙ 0 ∙ share

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AMASS: Archive of Motion Capture as Surface Shapes

Large datasets are the cornerstone of recent advances in computer vision...
04/05/2019 ∙ by Naureen Mahmood, et al. ∙ 0 ∙ share

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SimulCap : Single-View Human Performance Capture with Cloth Simulation

This paper proposes a new method for live free-viewpoint human performan...
03/15/2019 ∙ by Tao Yu, et al. ∙ 0 ∙ share

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Learning to Reconstruct People in Clothing from a Single RGB Camera

We present a learning-based model to infer the personalized 3D shape of ...
03/14/2019 ∙ by Thiemo Alldieck, et al. ∙ 0 ∙ share

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Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time

We demonstrate a novel deep neural network capable of reconstructing hum...
10/10/2018 ∙ by Yinghao Huang, et al. ∙ 0 ∙ share

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ReTiCaM: Real-time Human Performance Capture from Monocular Video

We present the first real-time human performance capture approach that r...
10/05/2018 ∙ by Marc Habermann, et al. ∙ 6 ∙ share

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Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation

Direct prediction of 3D body pose and shape remains a challenge even for...
08/17/2018 ∙ by Mohamed Omran, et al. ∙ 14 ∙ share

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Detailed Human Avatars from Monocular Video

We present a novel method for high detail-preserving human avatar creati...
08/03/2018 ∙ by Thiemo Alldieck, et al. ∙ 4 ∙ share

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Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources

To study the correlation between clothing garments and body shape, we co...
07/09/2018 ∙ by Hosnieh Sattar, et al. ∙ 0 ∙ share

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DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor

We propose DoubleFusion, a new real-time system that combines volumetric...
04/17/2018 ∙ by Tao Yu, et al. ∙ 0 ∙ share

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Video Based Reconstruction of 3D People Models

This paper describes how to obtain accurate 3D body models and texture o...
03/13/2018 ∙ by Thiemo Alldieck, et al. ∙ 0 ∙ share

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Single-Shot Multi-Person 3D Body Pose Estimation From Monocular RGB Input

We propose a new efficient single-shot method for multi-person 3D pose e...
12/09/2017 ∙ by Dushyant Mehta, et al. ∙ 0 ∙ share

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A Generative Model of People in Clothing

We present the first image-based generative model of people in clothing ...
05/11/2017 ∙ by Christoph Lassner, et al. ∙ 0 ∙ share

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Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

We address the problem of making human motion capture in the wild more p...
03/23/2017 ∙ by Timo von Marcard, et al. ∙ 1 ∙ share

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Detailed, accurate, human shape estimation from clothed 3D scan sequences

We address the problem of estimating human pose and body shape from 3D s...
03/13/2017 ∙ by Chao Zhang, et al. ∙ 0 ∙ share

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