, Akshay Mundra
Graduate Researcher
Max-Planck-Institut für Informatik
2021 - Present
Computer Vision Engineer
DreamVu Inc.
Undergraduate Researcher
Computer Vision Center, Barcelona
Fall 2017


  • LiveHand: Real-time and Photorealistic Neural Hand Rendering
    ICCV 2023

    Abstract ▾
    The human hand is the main medium through which we interact with our surroundings. Hence, its digitization is of uttermost importance, with direct applications in VR/AR, gaming, and media production amongst other areas. While there are several works modeling the geometry of hands, little attention has been paid to capturing photo-realistic appearance. Moreover, for applications in extended reality and gaming, real-time rendering is critical. We present the first neural- implicit approach to photo-realistically render hands in real-time. This is a challenging problem as hands are textured and undergo strong articulations with pose-dependent effects. However, we show that this aim is achievable through our carefully designed method. This includes training on a low- resolution rendering of a neural radiance field, together with a 3D-consistent super-resolution module and mesh-guided sampling and space canonicalization. We demonstrate a novel application of perceptual loss on the image space, which is critical for learning details accurately. We also show a live demo where we photo-realistically render the human hand in real-time for the first time, while also modeling pose- and view-dependent appearance effects. We ablate all our design choices and show that they optimize for rendering speed and quality.

    Code Project Page arXiv Thesis


Imitation Learning for Autonomous Driving Thesis Code

  • Developed a navigation system for an autonomous vehicle in a virtual environment, using imitation learning techniques.
  • Fine-tuned the model with real-world data to make it navigate in the real world.

Ray tracer in C++ Code Rendering Competition

  • Built a ray tracer in C++ with salient features such as acceleration structures and distribution ray tracing.
  • Showcased the ray tracer in a rendering competition.

Automated Traffic Control Monitoring Report Code

  • Developed an end-to-end ML pipeline to estimate traffic density from smartphone and vehicle dashcam images.
  • Pre-processed an in-the-wild dataset and trained a lightweight MobileNetV2 model on it.
  • Deployed the model on an android compatible application for real-time inferencing.

Multi-Frame Super Resolution for smartphone photography Report Code

  • Generated bursts of low-resolution images synthetically, imitating tremors common in hand-held photography.
  • Applied transfer learning to a Residual Feature Attention based model for multi-frame super-resolution.


Smart City Expo World Congress 2017

Showcased the work done on autonomous driving at the Smart City Expo World Congress in Barcelona.


Secured first​ ​position​ in APOGEE 2016 for the project Autonomous Solar Powered Grass Cutter. Received the prestigious APOGEE Award​ from BITSAA International for outstanding performance.

Merit-Cum-Need Scholarship at BITS Pilani

Received partial sponsership for tuition fees for all four years of undergraduate study at BITS Pilani.