Leonid Sigal

Faculty Member

Associate Professor, Department of Computer Science, University of British Columbia

Canada CIFAR Artificial Intelligence Chair

Leonid Sigal is an Associate Professor in the Department of Computer Science at the University of British Columbia. Prior to that, he was a Senior Research Scientist at Disney Research Pittsburgh and an Adjunct Faculty member at Carnegie Mellon University. He received his PhD in Computer Science from Brown University and completed a postdoctoral fellowship at the University of Toronto. Leonid also serves as scientific advisor for Borealis AI.

Leonid’s research interests are primarily in computer vision, machine learning, and computer graphics. His research focuses on problems of visual and multi-modal (visual, textural, auditory) understanding, reasoning and generation. This includes object recognition, scene understanding, articulated motion capture, action recognition, representation learning, manifold learning, transfer learning, character and cloth animation.

Research Interests

  • Computer Vision
  • Machine Learning
  • Computer Graphics
  • Neural Networks

Highlights

  • NSERC Canada Research Chair (Tier 2) in Computer Vision and Machine Learning (2018-2023)
  • Recipient of NSERC Discovery Accelerator Supplement (2018-2021)
  • Recipient of Killam Accelerator Research Fellowship (2021-2023)
  • Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) and Computer Vision and Image Understanding (CVIU)
  • Area chair for ECCV (2014, 2018), IEEE ICCV (2015), IEEE CVPR (2019)
  • Advisor, Borealis AI

Publications

Human pose estimation

Leonid Sigal

2021

Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by Gaussian-guided latent alignment

Jing Wang and Jiahong Chen and Jianzhe Lin and Leonid Sigal and Clarence W de Silva

2021

Referring transformer: A one-step approach to multi-task visual grounding

Muchen Li and Leonid Sigal

2021

Weakly-supervised audio-visual sound source detection and separation

Tanzila Rahman and Leonid Sigal

2021

PROVIDE: a probabilistic framework for unsupervised video decomposition

Polina Zablotskaia and Edoardo A Dominici and Leonid Sigal and Andreas M Lehrmann

2021

Guest editorial introduction to the special issue on large-scale visual sensor networks: architectures and applications

Paolo Spagnolo and Hamid Aghajan and George Bebis and Shaogang Gong and Amy Loutfi and Leonid Sigal and Wei-Shi Zheng

2021

TriBERT: Human-centric Audio-visual Representation Learning

Tanzila Rahman and Mengyu Yang and Leonid Sigal

2021

Probabilistic Label-Efficient Deep Generative Structures (PLEDGES)

Avi Pfeffer and Catherine Call and Frank Wood and Brad Rosenberg and Kirstin Bibbiani and Leonid Sigal and Ishaan Shah and Deniz Erdogmus and Sameer Singh and Jan W van de Meent

2021

Inve: Interactive neural video editing

Jiahui Huang and Leonid Sigal and Kwang Moo Yi and Oliver Wang and Joon-Young Lee

2023

Uncertainty guided adaptive warping for robust and efficient stereo matching

Junpeng Jing and Jiankun Li and Pengfei Xiong and Jiangyu Liu and Shuaicheng Liu and Yichen Guo and Xin Deng and Mai Xu and Lai Jiang and Leonid Sigal

2023

Dinn360: Deformable invertible neural network for latitude-aware 360deg image rescaling

Yichen Guo and Mai Xu and Lai Jiang and Leonid Sigal and Yunjin Chen

2023

Subpixel Deblurring of Anti‐Aliased Raster Clip‐Art

Jinfan Yang and Nicholas Vining and Shakiba Kheradmand and Nathan Carr and Leonid Sigal and Alla Sheffer

2023

GraphPNAS: Learning Probabilistic Graph Generators for Neural Architecture Search

Muchen Li and Jeffrey Yunfan Liu and Leonid Sigal and Renjie Liao

2023

Weakly-supervised Spatially Grounded Concept Learner for Few-Shot Learning

Gaurav Bhatt and Deepayan Das and Leonid Sigal and Vineeth N Balasubramanian

2023

Omnimatte3D: Associating Objects and Their Effects in Unconstrained Monocular Video

Mohammed Suhail and Erika Lu and Zhengqi Li and Noah Snavely and Leonid Sigal and Forrester Cole

2023

HyperSOR: Context-aware Graph Hypernetwork for Salient Object Ranking

Minglang Qiao and Mai Xu and Lai Jiang and Peng Lei and Shijie Wen and Yunjin Chen and Leonid Sigal

2024

Mitigating the Effect of Incidental Correlations on Part-based Learning

Gaurav Bhatt and Deepayan Das and Leonid Sigal and Vineeth N Balasubramanian

2024

Framework-agnostic Semantically-aware Global Reasoning for Segmentation

Mir Rayat Imtiaz Hossain and Leonid Sigal and James J Little

2024