Akshay Gadi Patil


Akshay Gadi Patil
Ph.D Student

GrUVi Lab
School of Computing Science
Simon Fraser University

Office: TASC-1 8004

About Me

I am a Ph.D student working in the area of AI-driven Computer Graphics, advised by Hao (Richard) Zhang.

My current research revolves around the geometric application of Deep Learning for content creation and understanding. Specifically, I focus on structural modeling of 3D Indoor Scenes and 2D Layouts.

Earlier, I graduated with an M.Tech in Electrical Engineering (Signal Processing) from IIT Gandhinagar, working with Shanmuganathan Raman, and also spent time as a visiting student at JAIST, Japan .

Work Experience

Research Intern (with Vova Kim)

May-Nov 2021

Applied Scientist Intern
Dec 2018 - March 2019

Publications [Scholar]

"Si falta pasiĆ³n no se encuentra la victoria".

- Rafa


LayoutGMN: Neural Graph Matching for Structural Layout Similarity

Akshay Gadi Patil, Manyi Li, Matthew Fisher, Manolis Savva, Hao Zhang
CVPR 2021

Paper, Supp, Code, Video


DR-KFS: A Differentiable Visual Similarity Metric for 3D Shape Reconstruction

Jiongchao Jin, Akshay Gadi Patil, Zhang Xiong, Hao Zhang
ECCV 2020

READ: Recursive Autoencoders for Document Layout Generation
Akshay Gadi Patil, Omri Ben-Eliezer, Or Perel, Hadar Averbuch-Elor
CVPR 2020 (Workshop on Text and Documents in Deep Learning Era, Best Paper Award )

Paper, Supplementary, Video

GRAINS: Generative Recursive Autoencoders for INdoor Scenes
Manyi Li, Akshay Gadi Patil, Kai Xu, Siddhartha Chaudhuri, Owais Khan, Ariel Shamir, Changhe Tu, Baoquan Chen, Daniel Cohen-Or, Hao Zhang
Transactions on Graphics (Special Issue of SIGGRAPH 2019)

Project Page
Language-Driven Synthesis of 3D Scenes Using Scene Databases
Rui Ma*, Akshay Gadi Patil*, Matthew Fisher, Manyi Li, Sören Pirk,
Binh-Son Hua, Sai-Kit Yeung, Xin Tong, Leonidas Guibas, Hao Zhang
SIGGRAPH-Asia, Tokyo, 2018 (*Co-first Authors)

Project Page, Media

Automatic Content-Aware Non-Photorealistic Rendering of Images
Akshay Gadi Patil, Shanmuganathan Raman
International Symposium on Visual Computing (ISVC), Las Vegas, 2016.
Tone Mapping HDR Images Using Local Texture and Brightness Measures
Akshay Gadi Patil, Shanmuganathan Raman
International Conference on Computer Vision and Image Processing (CVIP), 2016.


[NEW] Outstanding Reviewer Award, ICCV 2021

Best Paper Award at the CVPR Workshop on Texts and Documents in Deep Learning Era - 2020

SFU Computing Science Graduate Fellowship - 2016, 2018, 2019

SFU Graduate Fellowhsip - 2018

Century 21 Charlwood Family Graduate Scholarship - 2018, 2019

Helmut & Hugo Eppich Family Graduate Scholarship - 2021

Invited Talks

Computational Design and Fabrication Group, MIT - July 2021

Center for Mathematical Sciences and Applications Seminar, Harvard University - Dec 2020

Graphics and Vision Seminar, Tel-Aviv University - Dec 2018

Amazon - Dec 2018



Machine Learning: ICLR (2022, 21, 20), NeurIPS (2021)

Vision+Graphics: ICCV (2021), CVPR (2022, 21), ICPR (2020)

Computer Graphics: SIGGRAPH-Asia (2021), SIGGRAPH (2019), CGF (since 2020), TVCG (since 2019)

Student Volunteer (SV) at SIGGRAPH'18