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Firstname Lastname

Mallikarjun B R

(M. Byrasandra Ramalinga Reddy)
Max-Planck-Institut für Informatik
D6: Visual Computing and Artificial Intelligence
 office: Campus E1 4, Room 211B
Saarland Informatics Campus
66123 Saarbrücken
Germany
 email: mbr@mpi-inf.mpg.de
 phone: +49 681 9325 4056
 fax: +49 681 9325 4099

Research Interests

  • Computer Vision
  • Computer Graphics

Publications

PhotoApp: Photorealistic Appearance Editing of Head Portraits
M. B R, A. Tewari, A. Dib, T. Weyrich, B. Bickel, H-P. Seidel, H. Pfister, W. Matusik, L. Chevalier, M. Elgharib and C. Theobalt

ACM Transactions on Graphics (Proc. of SIGGRAPH 2021)   —   SIGGRAPH 2021

We present a method for high-quality appearance editing of head portraits. A supervised learning problem is designed in the latent space of the StyleGAN network. This allows for generalization to in-the-wild images, even when trained on a small light-stage dataset.
[paper] [project page]


Efficient and Differentiable Shadow Computation for Inverse Problems
L. Lyu, M. Habermann, L. Liu, M. B R, A. Tewari and C. Theobalt

Proc. International Conference on Computer Vision 2021   —   ICCV 2021

We propose an accurate yet efficient approach for differentiable visibility and soft shadow computation. Our approach is based on the spherical harmonics approximations of the scene illumination and visibility, where the occluding surface is approximated with spheres.
[paper] [project page]


Monocular Reconstruction of Neural Face Reflectance Fields
M. B R, A. Tewari, T-H. Oh, T. Weyrich, B. Bickel, H-P. Seidel, H. Pfister, W. Matusik, M. Elgharib and C. Theobalt

Proc. Computer Vision and Pattern Recognition 2021   —   CVPR 2021

We present a new neural representation for face reflectance where we can estimate all components of the reflectance responsible for the final appearance from a single monocular image.
[paper] [project page]


Learning Complete 3D Morphable Face Models from Images and Videos
M. B R, A. Tewari, H-P. Seidel, M. Elgharib and C. Theobalt

Proc. Computer Vision and Pattern Recognition 2021   —   CVPR 2021

We present the first approach to learn complete 3D models of face identity geometry, albedo and expression just from images and videos.
[paper] [project page]


PIE: Portrait Image Embedding for Semantic Control
A. Tewari, M. Elgharib, M. B R, F. Bernard, H-P. Seidel, P. Perez, M. Zollhöfer and C. Theobalt

ACM Transactions on Graphics (Proc. of SIGGRAPH Asia 2020)   —   SIGGRAPH Asia 2020

We present the first approach for embedding real portrait images in the latent space of StyleGAN which allows for intuitive editing of the head pose, facial expression, and scene illumination in the image.
[paper] [video] [Talk] [project page]


Education