Akshay Gadi Patil
Applied Scientist, Amazon
CS Ph.D, SFU
Email:
I am an Applied Scientist at Amazon Science in Sunnyvale, CA, working on GenAI for 3D.
I earned a Ph.D. degree from Simon Fraser University, adviced by Hao.
I work in the areas of 3D computer graphics and vision, developing computational models for generative
and interactive shape/scene understanding and geometric modeling problems.
Research Interests : Neural modeling of 3D shapes, 3D scenes and 2D documents, exploring different
representations, single and multi-modal, centered around generation, reconstruction, and interaction tasks.
Earlier, I graduated with a M.Tech in Electrical Engineering (Signal Processing) from IIT Gandhinagar, working with Shanmuganathan Raman. I was also a visiting student at JAIST, Japan .
3D Applied Scientist Intern
Aug 2022 - Jan 2023 |
Research Scientist Intern Summer 2021 |
Applied Scientist Intern
Dec 2018 - March 2019 |
"Si falta pasiĆ³n no se encuentra la victoria".
- Rafa
Active Coarse-to-Fine Segmentation of Moveable Parts from Real Images Ruiqi Wang, Akshay Gadi Patil, Fenggen Yu, Hao Zhang ECCV 2024 [Paper] |
Learning to Model 3D Indoor Scenes and Articulated Objects Akshay Gadi Patil Ph.D. Dissertation (Distinction: Defence and Thesis passed as is) Link |
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Advances in Data-Driven Analysis and Synthesis of 3D Indoor Scenes Akshay Gadi Patil, Supriya Gadi Patil, Manyi Li, Matthew Fisher, Manolis Savva, Hao Zhang Computer Graphics Forum (CGF) 2023 [Paper] |
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RoSI: Recovering 3D Shape Interiors from Few Articulation Images Akshay Gadi Patil, Yiming Qian, Shan Yang, Brian Jackson, Eric Bennett, Hao Zhang arXiv 2023 [Paper] |
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DiViNeT: 3D Reconstruction from Disparate Views via Neural Template Regularization Aiya Vora, Akshay Gadi Patil, Hao Zhang NeurIPS 2023 [Paper] |
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Coarse-to-Fine Active Segmentation of Interactable Parts in Real Scene Images Ruiqi Wang, Akshay Gadi Patil, Fenggen Yu, Hao Zhang arXiv 2023 [ Paper] |
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 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 |
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
Akshay Gadi Patil*, Rui Ma*, 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. 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. |
Outstanding Reviewer Award, ECCV 2022
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
Stanford Vision and Learning Lab - May 2023
Max Planck Institute for Informatics - March 2023
Facebook - May 2022
Computational Design and Fabrication Group, MIT - July 2021
Young Scientists' Seminar, CMSA, Harvard University - Dec 2020
Graphics and Vision Seminar, Tel Aviv University - Dec 2018
Amazon - Dec 2018
Co-organizer of Learning to Generate 3D Shapes and Scenes workshop at ECCV 2022
Area Chair
WACV (2025)
Reviewer
Machine Learning: ICML (2022-24), ICLR (2020-24), NeurIPS (2021-24)
Vision+Graphics: ECCV (2022, 24), ICCV (2021, 23), CVPR (2021-24)
Computer Graphics: SIGGRAPH (2019, 22, 24), SIGGRAPH Asia (2021, 22), Eurographics (2022), CGF (since 2020)
Student Volunteer (SV) at SIGGRAPH'18