Computer Vision - Where are we?

Detailed ICVSS 2019 Programme

LECTURES

Speakers	Syllabus	Titles & Abstracts
Alexei Efros UC Berkeley, US	Deep Learning for Vision	Deep Learning for Vision: the Hype, the Magic, and Open Challenges
Irfan Essa Georgia Institute of Technology and Google Research, US	Video Analysis, Video Compression, Registration and Alignment, Video Segmentation and Tracking, Action/Activity Recognition	Computational Video: Can we just extend all image-based approaches to video by applying image analysis to all the frames?
Andreas Geiger University of Tübingen and MPI-IS Tübingen, DE	3D Reconstruction, Graphical Models, 3D Representations, Deep Learning	Probabilistic and Deep Models for 3D Reconstruction
Kristen Grauman University of Texas at Austin and Facebook AI Research, US	First Person Vision, Anticipation	First-Person Perception by Anticipating the Unseen and Unheard
Abhinav Gupta Carnegie Mellon University, US	Self-supervised Learning, Visual Representations, Perception and Action	Self-supervised Learning of Visual Representations for Perception and Action
Phillip Isola Massachusetts Institute of Technology, US	Generative Models, Image Syntesis	Image synthesis with deep generative models
Alex Kendall Wayve and University of Cambridge, UK	Autonomous Driving, domain adaptation, imitation learning, reinforcement learning	Training Deep Learning to Drive in the Real World with Computer Vision
Ira Kemelmacher-Shlizerman Allen School of Computer Science, UW, US	AR/VR applications	People modeling and AR/VR applications
Jitendra Malik University of California at Berkeley, US	3D vision, recognition, reconstruction, Perception and control, Hilbert problems of computer vision	What problems does computer vision need to solve?
Richard Newcombe Facebook Reality Labs, US	Spatial AI	Spatial AI at the Frontier of XR, Robotics & AI Assistants
Torsten Sattler Chalmers University of Technology, SE	Visual Localization	Visual Localization
Davide Scaramuzza ETH Zürich, CH	Robot Vision	Robot Vision: from Frame-based to Event-based Cameras
Bernt Schiele Max Planck Institute, DE	Privacy and Security, Computer Vision, Machine Learning	The Bright and Dark Sides of Computer Vision and Machine Learning — Challenges and Opportunities for Privacy and Security
Stefano Soatto Amazon and University of California Los Angeles, USA	Learning Representations	Learning Representations: From Shannon to Fisher to Bayes to Kolmogorov via Deep Networks and the Implications to Visual Information Processing in Biology and in the Cloud
Federico Tombari Technical University of Munich, DE	3D descriptors, 3D object detection, 6DoF pose estimation, 3D reconstruction, SLAM	Features for 6D pose and 3D reconstruction: towards lightweight, monocular and unsupervised

READING GROUP (WITH PRIZE!)

Speakers	Syllabus	Rules of Engagement
Stefano Soatto Amazon and University of California Los Angeles, USA	Reading Group Competition	Rules of Engagement

ESSAY COMPETITION (WITH PRIZE!)

Speakers	Syllabus	Rules of Engagement
Fabio Galasso OSRAM Corporate Technology, DE	Essay Competition	Rules of Engagement

INDUSTRY MEETS STUDENTS

Industrial Panel

POSTER SESSION (WITH PRIZE!)

POSTERS SUBMITTED TO ICVSS 2019

Detailed ICVSS 2019 Programme

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