Award Winners

CRV Conference

CRV Award Committee

  • Michael Jenkin, York University (Chair)
  • Steven Waslander, University of Toronto
  • Helge Rhodin, University of British Columbia
  • Hsiu-Chin Lin, McGill University

Winners

Best Computer Vision Paper

Occluded Text detection and Recognition in the Wild
Zobeir Raisi (University of Waterloo)
John Zelek (University of Waterloo)

Best Robotics Paper

Occlusion-Aware Self-Supervised Stereo Matching with Confidence Guided Raw Disparity Fusion
Xiule Fan (University of Waterloo)
Soo Jeon (University of Waterloo)
Baris Fidan (University of Waterloo)

John Barron Dissertation Award in Computer Vision (2021)

Dr. Mohmoud Afifi
York University
Image Color Correction, Enhancement, and Editing

John Barron Dissertation Award in Robotics (2021)

Dr. Sandeep Manjanna
McGill University
Multi-Robot Planning Strategies for Non-myopic Spatial Sampling

 

 

AI Conference

CAIAC Lifetime Achievement Award

Prof. Fahiem Baccus, University of Toronto and Prof. François Laviolette, Université Laval

CAIAC Distinguished Service Award

Prof. Malek Mouhoub, University of Regina

CAIAC Best PhD Dissertation

Dr. Jincheng Mei, University of Alberta, Non-uniform Analysis for Non-convex Optimization in Machine Learning

CAIAC Best MSc Theses

Amin Bigdeli, Toronto Metropolitan University (formerly Ryerson University), Exploration and Mitigation of Stereotypical Gender Biases in Information Retrieval Systems
and
Shivam Garg, University of Alberta, Analysis of an Alternate Policy Gradient Estimator for Softmax Policies

Canadian AI Best Paper Awards

  • Jaël Champagne Gareau, Éric Beaudry and Vladimir Makarenkov. Cache-Efficient Memory Representation of Markov Decision Processes
  • Basile Tousside, Janis Mohr and Jörg Frochte. Group and Exclusive Sparse Regularization-based Continual Learning of CNNs
  • Kiarash Zahirnia, Oliver Schulte, Ke Li, Ankita Sakhuja and Parmis Naddaf. Deep Learning of Latent Edge Types from Relational Data
  • Zhenyu Liao, Charupriya Sharma, Dongshu Luo and Peter van Beek. An empirical study of scoring functions for learning Bayesian networks in model averaging
  • Ali Abbasi Tadi, Luis Rueda and Dima Alhadidi. NICASN: Non-negative Matrix Factorization and Independent Component Analysis for Clustering Social Networks

Canadian AI Best Student Paper Awards

Kiarash Zahirnia, Oliver Schulte, Ke Li, Ankita Sakhuja and Parmis Naddaf. Deep Learning of Latent Edge Types from Relational Data
and
Basile Tousside, Janis Mohr and Jörg Frochte. Group and Exclusive Sparse Regularization-based Continual Learning of CNNs