Akshay Gadi Patil
Ph.D Student
GrUVi Lab
School of Computing Science
Simon Fraser University
Email:
Office: TASC-1 8004
I am a Ph.D student working in the area of 3D computer graphics, advised by Hao (Richard) Zhang.
I broadly work on the applications of deep learning to shape/scene understanding and geometric modeling problems.
Specifically, I focus on the structural modeling of 3D shapes, indoor scenes and 2D layouts.
Earlier, I graduated with an M.Tech in Electrical Engineering (Signal Processing) from IIT Gandhinagar, working with Shanmuganathan Raman. I was also a visiting student at JAIST, Japan .
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Research Intern May-Nov 2021 |
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Applied Scientist Intern
Dec 2018 - March 2019 |
"Si falta pasión no se encuentra la victoria".
- Rafa
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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 |
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DR-KFS: A Differentiable Visual Similarity Metric for 3D Shape Reconstruction Jiongchao Jin, Akshay Gadi Patil, Zhang Xiong, Hao Zhang ECCV 2020 Paper |
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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 |
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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 |
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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 |
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Automatic Content-Aware Non-Photorealistic Rendering of Images
Akshay Gadi Patil, Shanmuganathan Raman International Symposium on Visual Computing (ISVC), Las Vegas, 2016. Paper |
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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
Facebook - May 2022
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
Reviewer
Machine Learning: ICML (2022), ICLR (2020-22), NeurIPS (2021-22)
Vision+Graphics: ECCV (2022), ICCV (2021), CVPR (2022, 21)
Computer Graphics: SIGGRAPH (2022, 2019), SIGGRAPH Asia (2022, 21), Eurographics (2022), CGF (since 2020), TVCG (since 2019)
Misc.
[NEW] Co-organizer of this workshop at ECCV 2022
Student Volunteer (SV) at SIGGRAPH'18