Mayur Deshmukh

Saarbrucken, Germany


I am a Research Assistant at Max Planck Institute for Informatics in Saarbrucken, Germany, and a Master's student in Computer Science at Saarland University. My research focuses on Computer Vision and Deep Learning, Beyond work, I enjoy hiking, photography, and gaming.

Portrait of Mayur Deshmukh

News

  • Feb 2026: Paper accepted at CVPR 2026.
  • Nov 2025: Paper accepted at 3DV 2026.

Research

My research focus lies at the intersection of Computer Vision and Deep Learning. In particular, I am interested in the following topics:

  • Neural Rendering and 3D Head Avatars
  • Human Pose and Motion Generation
  • Egocentric 3D Vision
  • Multi-modal Generative AI
  • Event Cameras

Publications

E-3DPSM teaser GIF
E-3DPSM: A State Machine for Event-based Egocentric 3D Human Pose Estimation

Mayur Deshmukh, Hiroyasu Akada, Helge Rhodin, Christian Theobalt, Vladislav Golyanik

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026, Denver

Paper Project Page Code (Coming soon)

We introduce E3DPSM (Event-based 3D Pose State Machine), an event-driven continuous pose state machine for egocentric 3D human pose estimation. By aligning motion dynamics with asynchronous event streams, it produces stable, drift-free pose estimates in real time (80 Hz). Our method sets a new state of the art, improving accuracy by up to 19% and temporal stability by 2.7x.

GRMM teaser GIF
GRMM: Real-Time High-Fidelity Gaussian Morphable Head Model with Learned Residuals

Mohit Mendiratta, Mayur Deshmukh, Kartik Teotia, Vladislav Golyanik, Adam Kortylewski, Christian Theobalt

International Conference on 3D Vision (3DV), 2026, Vancouver

Paper Project Page Code (Coming soon)

Our method, GRMM (Gaussian Residual Morphable Model), generates high-fidelity 3D head avatars in real time by combining a mesh-based morphable prior with learned Gaussian residuals. This design captures fine geometric and appearance details while maintaining disentangled control over identity and expression, enabling photorealistic and expressive facial synthesis.


Projects


PhotonPulse

PhotonPulse is a C++ physically based renderer with support for cameras, BSDFs, samplers, lights, integrators, and post-processing features such as denoising and bloom.

GitHub

SceneChat

SceneChat is a text-driven scene generation pipeline that turns a natural language description into a structured room layout, previews the layout in Blender, and can generate 3D assets for the objects in the scene.

GitHub

Semantic Perceptual Image Compression

This project implements a semantic, perceptual image compression pipeline that uses a convolutional model to identify regions of interest in an image and allocate compression quality accordingly.

GitHub

Education & Experience


  • [July 2024 - Present] Research Assistant, Max Planck Institute for Informatics (Saarbrucken, Germany)
  • [Oct 2023 - Present] Master student, Computer Science, Saarland University (Saarbrucken, Germany)
  • [Sept 2020 - Aug 2023] Software Engineer, Josh Software, Inc. (Pune, India)
  • [Jan 2020 - Mar 2020] Intern, Josh Software, Inc. (Pune, India)
  • [June 2016 - May 2020] Bachelor student, Computer Engineering, Savitribai Phule Pune University (Pune, India)
© Mayur Deshmukh 2026 / Design: OpenAI Codex