Aakash KT


I am a second year Ph.D student at CVIT, IIIT Hyderabad, supervised by Dr. P J Narayanan (Funded by the KCIS fellowship).
Previously, I completed my MS by research at IIIT Hyderabad, which is also where I completed my BTech in Computer Science Engineering.
My research involves playing around with the light transport equation for real-time performance, differentiable rendering and neural rendering (in other words, I work on Computer Vision/Computer Graphics and Machine Learning/Deep Learning.).
Welcome to my page!

Resume / Email / Google Scholar / Twitter


  • Our paper "Fast Analytic Soft Shadows from Area Lights" has been accepted to EGSR 2021! [Jun 2021]
  • I have joined as a Ph.D student at CVIT, IIIT Hyderabad, supervised by Dr. P J Narayanan. My Ph.D is funded by the KCIS fellowship. Curious as to why I decided to do this? See here. [Aug. 2020]
  • I was to join the GraphDeco research group @ Inria (Sophia Antipolis, France), as a pre-doctoral candidate from September 2020, supervised by Dr. George Drettakis and Dr. Adrien Bousseau. [Rescinded due to COVID]


A complete list of publications.[Updated 12/2021].

Fast Analytic Soft Shadows from Area Lights

Aakash KT, Parikshit Sakurikar, P. J. Narayanan

Eurographics Symposium on Rendering (EGSR), 2021

We present an analytical solution for soft shadows from area lights, which naturally produces noise-free renderings as compared to equivalent stochastic methods. A structured approach to analytically compute soft shadows from spherical projections of lights and occluders with any 3D shape and efficiently for convex 3D shapes.

[Publisher's Version] [Author's Version] [EGSR Talk Video] [Code] [bibtex]

Neural View Synthesis with Appearance Editing from Unstructured Images

Pulkit Gera, Aakash KT, Dhawal Sirikonda, Parikshit Sakurikar, P. J. Narayanan

Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2021

We present a neural rendering framework for simultaneous view synthesis and appearance editing of a scene with known environmental illumination captured using a mobile camera. Our approach explicitly disentangles the appearance and learns a lighting representation that is independent of it. We show results of editing the appearance of real scenes in interesting and non-trivial ways.

[Project Page] [Publisher's Version] [arXiv] [Code] [bibtex]

A Flexible Neural Renderer for Material Visualization

Aakash KT, Parikshit Sakurikar, Saurabh Saini, P. J. Narayanan

ACM SIGGRAPH Asia Technical Briefs, 2019

Photo realism in computer generated imagery is crucially dependent on how well an artist is able to recreate real-world materials in the scene. We propose a convolutional neural network based workflow which generates high-quality ray traced material visualizations on a shaderball, in real-time.

[Project page] [Author's Version] [Publisher's Version] [Code/Data] [arXiv] [bibtex]

Other Activities

  • Tertiary reviewer for Pacific Graphics (PG) 2021.
  • Currently mentoring one MS and one undergraduate student.
  • Assisted with the interview prep of my advisor Dr. P J Narayanan with Dr. Edwin Catmull for ACM India. See here.

Unique visitors

counter free