Akshay Gadi Patil

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 .

Publications [Scholar]

"Si falta pasión no se encuentra la victoria".

- Rafa

2021

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

2020

	DR-KFS: A Differentiable Visual Similarity Metric for 3D Shape Reconstruction Jiongchao Jin, Akshay Gadi Patil, Zhang Xiong, Hao Zhang ECCV 2020 Paper
	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

2018

	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

2016

	Automatic Content-Aware Non-Photorealistic Rendering of Images Akshay Gadi Patil, Shanmuganathan Raman International Symposium on Visual Computing (ISVC), Las Vegas, 2016. Paper
	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.

Awards

[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