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Synthesis Lectures on Computer Vision

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  1. Structured Representation Learning

    Structured Representation Learning

    Yue Song, Thomas Anderson Keller, Nicu Sebe, Max Welling · 2026

  2. Normalization Techniques in Deep Learning

    Normalization Techniques in Deep Learning

    Lei Huang · 2026

  3. Probabilistic and Biologically Inspired Feature Representations

    Probabilistic and Biologically Inspired Feature Representations

    Michael Felsberg · 2018

  4. Image-Based Modeling of Plants and Trees

    Image-Based Modeling of Plants and Trees

    Sing Bang Kang, Long Quan · 2009

  5. Boosting-Based Face Detection and Adaptation

    Boosting-Based Face Detection and Adaptation

    Cha Zhang, Zhengyou Zhang · 2010

  6. Deformable Surface 3D Reconstruction from Monocular Images

    Deformable Surface 3D Reconstruction from Monocular Images

    Mathieu Salzmann, Pascal Fua · 2010

  7. Camera Networks

    Camera Networks

    Amit K Roy-Chowdhury, Bi Song · 2012

  8. Fine-Grained Image Analysis: Modern Approaches

    Fine-Grained Image Analysis: Modern Approaches

    Xiu-Shen Wei · 2023

  9. Vision-Based Interaction

    Vision-Based Interaction

    Gang Hua, Matthew Turk · 2013

  10. Background Subtraction

    Background Subtraction

    Ahmed Elgammal · 2014

  11. Computational Methods for Integrating Vision and Language

    Computational Methods for Integrating Vision and Language

    Kenichi Kanatani, Yasuyuki Sugaya · 2016

  12. Ellipse Fitting for Computer Vision

    Ellipse Fitting for Computer Vision

    Kenichi Kanatani, Yasuyuki Sugaya, Yasushi Kanazawa · 2016

  13. Advances in Face Presentation Attack Detection

    Advances in Face Presentation Attack Detection

    Jun Wan, Guodong Guo, Sergio Escalera, Hugo Jair Escalante, Stan Z. Li · 2023

  14. Data Association for Multi-Object Visual Tracking

    Data Association for Multi-Object Visual Tracking

    Margrit Betke, Zheng Wu · 2016

  15. Extreme Value Theory-Based Methods for Visual Recognition

    Extreme Value Theory-Based Methods for Visual Recognition

    Walter J. Scheirer · 2017

  16. Maximum Consensus Problem

    Maximum Consensus Problem

    Tat-Jun Chin, David Suter · 2017

  17. Elastic Shape Analysis of Three-Dimensional Objects

    Elastic Shape Analysis of Three-Dimensional Objects

    Ian H. Jermyn, Sebastian Kurtek, Hamid Laga, Anuj Srivastava · 2017

  18. Unifying Framework for Formal Theories of Novelty

    Unifying Framework for Formal Theories of Novelty

    Terrance Boult, Walter Scheirer · 2023

  19. Covariances in Computer Vision and Machine Learning

    Covariances in Computer Vision and Machine Learning

    Hà Quang Minh, Vittorio Murino · 2017

  20. Guide to Convolutional Neural Networks for Computer Vision

    Guide to Convolutional Neural Networks for Computer Vision

    Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun · 2018

  21. Computational Texture and Patterns

    Computational Texture and Patterns

    Kristin J. Dana · 2018

  22. Multi-Modal Face Presentation Attack Detection

    Multi-Modal Face Presentation Attack Detection

    Jun Wan, Guodong Guo, Sergio Escalera, Hugo Jair Escalante, Stan Z. Li · 2020

  23. Video Object Segmentation

    Video Object Segmentation

    Ning Xu, Weiyao Lin, Xiankai Lu, Yunchao Wei · 2023

  24. Person Re-Identification with Limited Supervision

    Person Re-Identification with Limited Supervision

    Rameswar Panda, Amit K. Roy-Chowdhury · 2021

  25. Computer Vision in the Infrared Spectrum

    Computer Vision in the Infrared Spectrum

    Michael Teutsch, Angel D. Sappa, Riad I. Hammoud · 2021

  26. Video Object Tracking

    Video Object Tracking

    Ning Xu, Weiyao Lin, Xiankai Lu, Yunchao Wei · 2023

  27. Advances in Multimodal Information Retrieval and Generation

    Advances in Multimodal Information Retrieval and Generation

    Man Luo, Tejas Gokhale, Neeraj Varshney, Yezhou Yang, Chitta Baral · 2024

  28. Visual Domain Adaptation in the Deep Learning Era

    Visual Domain Adaptation in the Deep Learning Era

    Gabriela Csurka, Timothy M. Hospedales, Mathieu Salzmann, Tatiana Tommasi · 2022

  29. Learning-from-Observation 2.0

    Learning-from-Observation 2.0

    Katsushi Ikeuchi, Naoki Wake, Jun Takamatsu, Kazuhiro Sasabuchi · 2025

  30. Machine Unlearning for Governance of Foundation Models

    Machine Unlearning for Governance of Foundation Models

    Sijia Liu, Yang Liu, Nathalie Baracaldo · 2026