Challenge is held on Kaggle
Feb. 2 2018Results are released
May 27 2018Held with CVPR’18
Jun. 18 2018, 13:30 - 17:30, MDTAndre Araujo
Tobias Weyand
Josef Sivic (INRIA / CTU) (Hosted by Ondra Chum)
Learnable Representations for Estimating Visual Correspondence
Andre Araujo and Tobias Weyand
Herve Jegou (FAIR) (Hosted by Ondra Chum)
Trends in Large-Scale Similarity Search
Tobias Weyand
Senior researcher at Inria and a principal investigator at Czech Technical University in Prague
Finding visual correspondence is one of the fundamental image understanding problems. It is a challenging task due to strong appearance differences between the corresponding scene elements caused by, for example, changes in camera viewpoint and illumination, intra-class variation, or scenes changes over time. In this talk, I will discuss our recently developed learnable representations for visual correspondence tasks with applications to category-level object alignment, observer localization in large-scale indoor environments with textureless areas and repetitive patterns, and place recognition across day/night illumination or changes of weather and seasons.
Research Lead with Facebook AI Research
In this talk, I will present some recent trends in the area of similarity search. I will first review the techniques that are routinely employed to index and search billions of image descriptors, such as local features or more global representations extracted from CNN architectures. Then I will present recent advances based on graph-descent algorithms, as well as emerging methods for indexing with neural networks.
Associate Professor, Seoul National University (Primary Contact)
Software Engineer, Google (Primary Contact)
Professor, Columbia University
Associate Professor, Czech Technical University
Senior Researcher, ETH
Software Engineer, Google
Postdoc, Czech Technical University
Software Engineer, Google
Postdoc, Columbia University
© 2019 Landmarks18
We thank Jalpc for the jekyll template
