News

Jun, 2023:
Papers accepted to ICCV 2023 and TMLR.
Dec, 2022:
Papers accepted to ECCV 2022 and to CVPR 2022.
Apr, 2022:
Papers accepted to ICLR 2022 and to AISTATS 2022.
Nov, 2021:
2 papers accepted to NeurIPS 2021.
May, 2021:
f-DAL paper accepted to ICML 2021.
Dec, 2020:
1 paper accepted to NeurIPS 2020.
Mar, 2020:
1 paper accepted to CVPR 2020 (Oral Presentation).
Jan, 2020:
July, 2019:
3 papers accepted to ICCV 2019. 2 orals, 1 poster.
Jun, 2019:
STEAL (CVPR2019) is featured in the media: VentureBeat, Nvidia Developer Center, Edgy and, ... .
Jun, 2019:
Gave a talk at CVPR2019, Devil is in the Edges (STEAL).
May, 2019:
Released Inference Code for STEAL.
Mar, 2019:
2 papers accepted to CVPR 2019. 1 oral, 1 poster.
Feb, 2019:
1 paper accepted to ICRA 2019.
Jan, 2019:
Polygon-RNN++ and Training DeepNets with Synth Data featured as Breakthrough Developments of 2017-2018 by MIT DeepLearning.
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Jun, 2018:
Jun, 2018:
Polygon-RNN++ and Training DeepNets with Synth Data featured as "the 10 coolest papers from CVPR2018" by TowardsDataScience.

Selected Publications

University of Toronto
(PhD Thesis)

In International Conference on Learning Representations (ICLR), 2022

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

In Conference on Neural Information Processing Systems (NeurIPS), 2021

In Conference on Neural Information Processing Systems (NeurIPS), 2021

In Neural Information Processing Systems (NeurIPS), 2020

In Computer Vision and Pattern Recognition (CVPR), 2020
(Oral Presentation)

In International Conference of Computer Vision (ICCV), 2019

In International Conference of Computer Vision (ICCV), 2019
(Oral Presentation)

In Computer Vision and Pattern Recognition (CVPR), 2019

In International Conference on Robotics and Automation (ICRA), 2019

In Computer Vision and Pattern Recognition (CVPR), 2018

In Computer Vision and Pattern Recognition Autonomus Driving Workshop (CVPR), 2018

In Neural Information Processing Systems (NeurIPS) workshop on Constructive Machine Learning, 2016