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NetVLAD: CNN architecture for weakly supervised place recognition Our trained NetVLAD descriptor correctly recognizes the location (b) of the query photograph (a) despite the large amount of clutter (people, cars), changes in viewpoint and completely different illumination (night vs daytime). Abstract We tackle the problem of large scale visual place recognition, where the task is to quickly and a
www.di.ens.fr/~miech
Sortable and searchable compilation of video dataset Author: Antoine Miech Last Update: 17 October 2019
www.di.ens.fr/~laptev
We provide a dataset with 12 classes of human actions and 10 classes of scenes distributed over 3669 video clips and approximately 20.1 hours of video in total. The dataset intends to provide a comprehensive benchmark for human action recognition in realistic and challenging settings. The dataset is composed of video clips from 69 movies (see the list of movies below). A part of this dataset was o
Many multi-view stereo (MVS) algorithms do not scale well to a large number of input images (lack of computational and memory resources). This software (CMVS) takes the output of a structure-from-motion (SfM) software as input, then decomposes the input images into a set of image clusters of managable size. An MVS software can be used to process each cluster independently and in parallel, where th
Yasutaka Furukawa - University of Illinois at Urbana-Champaign, University of Washington Jean Ponce - University of Illinois at Urbana-Champaign, Ecole Normale Supérieure New! Please refer to our new software Clustering Views for Multi-view Stereo (CMVS). CMVS contains PMVS2 and have additional useful features (e.g., no need to worry about memory limitation any more.) PMVS is a multi-view stereo s
www.di.ens.fr/~cousot
This introduction to static analysis by abstract interpretation has the objective of being simple, intuitive and informal. More technical introductions as well as bibliographic references are provided in [1,2,3]. A 30mn video (in French) can also be useful. 1. Concrete semantics of programs The concrete semantics of programs formalizes the set of all possible executions of this program in all pos
Abstract Interpretation Web page maintained by P. Cousot Last update: Aug 5, 2008 Contents 1 Introduction to Abstract Interpretation 2 What can be formalized by abstract interpretation? 2.1 Syntax 2.2 Semantics 2.3 Proofs 2.4 Static analysis 2.5 Data-flow Analysis 2.6 Control-flow Analysis 2.7 Types 2.8 Model-checking 2.9 Predicate abstraction 2.10 Counter-example-based refinement 2.11
Image classification, Ivan Laptev, Cordelia Schmid, Josef Sivic and Andrew Zisserman Tuesday, July 26, 16.30-17.30 Category-level localization: Face detection, Ivan Laptev, Cordelia Schmid, Josef Sivic Thursday, July 28, 18.00-19.00 Supervised learning, SVMs, kernel methods, Francis Bach Instance-level recognition (part1, part2), Cordelia Schmid and Josef Sivic Large-scale visual search (part1, pa
www.di.ens.fr/~zappa
Modelling and verifying algorithms in Coq: an introduction CEA-EDF-INRIA summer school, Paris, 7-11 June 2010. Speakers: Yves Bertot, Pierre Casteran, Pierre Letouzey, Assia Mahboubi. Assistants: Stéphane Glondu, Francesco Zappa Nardelli. The Coq Proof Assistant can be downloaded from here. The files of these lectures have been tested with version 8.2pl1 but should work with any 8.2 (or later) ver
www.di.ens.fr/~mairal
Tutorial on Sparse Coding and Dictionary Learning for Image Analysis, CVPR 2010 General Information Organizers Francis Bach (INRIA) Julien Mairal (INRIA) Jean Ponce (Ecole Normale Supérieure) Guillermo Sapiro (University of Minnesota) Time Monday 14th, June 2010, Afternoon Duration 4 hours Short Description Sparse coding calls for modelling data vectors as a linear combination of a few elements fr
www.di.ens.fr/~fbach
Sparse methods for machine learning: Theory and algorithms NIPS 2009 Tutorial Francis Bach (INRIA - Ecole Normale Supérieure, Paris) Slides (6.5 Mb) Slides (low-resolution images - 1.9 Mb) Abstract Regularization by the L1-norm has attracted a lot of interest in recent years in statistics, machine learning and signal processing. In the context of least-square linear regression, the problem is usua
Bertille Follain, co-advised with Umut Simsekli Marc Lambert, co-advised with Silvère Bonnabel Ivan Lerner, co-advised with Anita Burgun et Antoine Neuraz Simon Martin, co-advised with Giulio Biroli Céline Moucer, co-advised with Adrien Taylor Anant Raj, co-advised with Maxim Raginsky Corbinian Schlosser, co-advised with Alessandro Rudi Lawrence Stewart, co-advised with Jean-Philippe Vert Alumni M
www.di.ens.fr/~longo
Selected publications by Giuseppe Longo, after 1990 available as .dvi, .ps (some gzipped) or .pdf files by ftp and http 1 - Mathematical Logic and Computer Science. 2 - Cognition and Foundations of Mathematical Knowledge. 3 - Theoretical Biology. 4 - Interfaces Computability, Physics and Biology. 5 - Minima Philosophica. 6 - Minima Economica. 7 - 1980's: Some of the
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