Search Results for author: Marcus Magnor

Found 8 papers, 5 papers with code

Sampling Based Scene-Space Video Processing

no code implementations5 Feb 2021 Felix Klose, Oliver Wang, Jean-Charles Bazin, Marcus Magnor, Alexander Sorkine-Hornung

We present a novel, sampling-based framework for processing video that enables high-quality scene-space video effects in the presence of inevitable errors in depth and camera pose estimation.

Deblurring Denoising +2

High-Fidelity Neural Human Motion Transfer from Monocular Video

1 code implementation CVPR 2021 Moritz Kappel, Vladislav Golyanik, Mohamed Elgharib, Jann-Ole Henningson, Hans-Peter Seidel, Susana Castillo, Christian Theobalt, Marcus Magnor

We address these limitations for the first time in the literature and present a new framework which performs high-fidelity and temporally-consistent human motion transfer with natural pose-dependent non-rigid deformations, for several types of loose garments.

Image Generation

Tex2Shape: Detailed Full Human Body Geometry From a Single Image

1 code implementation ICCV 2019 Thiemo Alldieck, Gerard Pons-Moll, Christian Theobalt, Marcus Magnor

From a partial texture, we estimate detailed normal and vector displacement maps, which can be applied to a low-resolution smooth body model to add detail and clothing.

Image-to-Image Translation

Learning to Reconstruct People in Clothing from a Single RGB Camera

1 code implementation CVPR 2019 Thiemo Alldieck, Marcus Magnor, Bharat Lal Bhatnagar, Christian Theobalt, Gerard Pons-Moll

We present a learning-based model to infer the personalized 3D shape of people from a few frames (1-8) of a monocular video in which the person is moving, in less than 10 seconds with a reconstruction accuracy of 5mm.

Detailed Human Avatars from Monocular Video

1 code implementation3 Aug 2018 Thiemo Alldieck, Marcus Magnor, Weipeng Xu, Christian Theobalt, Gerard Pons-Moll

We present a novel method for high detail-preserving human avatar creation from monocular video.

Video Based Reconstruction of 3D People Models

1 code implementation CVPR 2018 Thiemo Alldieck, Marcus Magnor, Weipeng Xu, Christian Theobalt, Gerard Pons-Moll

This paper describes how to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving.

3D Reconstruction Virtual Try-on

Optical Flow-based 3D Human Motion Estimation from Monocular Video

no code implementations1 Mar 2017 Thiemo Alldieck, Marc Kassubeck, Marcus Magnor

Under the assumption that starting from an initial pose optical flow constrains subsequent human motion, we exploit flow to find temporally coherent human poses of a motion sequence.

Motion Estimation Optical Flow Estimation

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