THOTH Reading Group

Access information for our usual meeting places: INRIA Montbonnot and XRCE Meylan.

Table of contents:




Sessions in 2016

Subject of meeting Materials Date & time Place Speaker
Max Jaderberg, Karen Simonyan, Andrew Zisserman, Koray Kavukcuoglu
Spatial Transformer Networks
paper
02/02/2016 11:00 am
Inria-Montbonnot : F107 Mattis Paulin
O. Vinyals and A. Toshev and S. Bengio and D. Erhan
Show and tell: A neural image caption generator
A. Karpathy and L. Fei-Fei
Deep Visual-Semantic Alignments for Generating Image Descriptions
paper 1
paper 2
01/19/2015 11:00 am
Inria-Montbonnot : A103 Marco Pedersoli



LEAR-XRCE reading group (2012-2015)

Sessions in 2015

Subject of meeting Materials Date & time Place Speaker

R-CNN and friends: fast, faster, better, stronger object detection
paper 09/15/2015 2:30 pm
Inria-Montbonnot : F107 Jon Almazan
Artem Babenko, Anton Slesarev, Alexandr Chigorin, Victor Lempitsky
Neural Codes for Image Retrieval
paper slides 07/07/2015
Inria, Montbonnot, F107 Mattis Paulin
Jason Yosinski,Jeff Clune,Yoshua Bengio, Hod Lipson
>How transferable are features in deep neural networks?
paper slides
Sergey Zagoruyko, Nikos Komodakis
Learning to Compare Image Patches via Convolutional Neural Networks
paper slides Matthijs Douze
Julien Mairal, Piotr Koniusz, Zaid Harchaoui, Cordelia Schmid
Convolutional Kernel Networks
paper slides 06/16/2015
XEROX Julien Mairal
Karen Simonyan, Andrew Zisserman
Very Deep Convolutional Networks for Large-Scale Image Recognition
paper slides 05/19/2015
XEROX Adrien Gaidon
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
Going Deeper with Convolutions
paper slides Adrien Gaidon
Jeff Donahue Lisa Anne Hendricks Sergio Guadarrama Marcus Rohrbach
Long-term recurrent convolutional networks for visual recognition and description
paper slides 05/03/2015
INRIA A107 Nicolas Chesneau
Arjun Jain, Jonathan Tompson, Yann LeCun and Christoph Bregler
MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
paper slides Vladyslav Sydorov
Karen Simonyan Andrew Zisserman
Two-Stream Convolutional Networks for Action Recognition in Videos
paper slides 05/03/2015 INRIA A107 Daan Wynen
Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, Li Fei-Fei
Large-scale Video Classification with Convolutional Neural Networks
paper slides Philippe Weinzaepfel

Sessions in 2014

Subject of meeting Materials Date & time Place Speaker
J. Mairal
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization. (NIPS 2013)
Optimization with First-Order Surrogate Functions. (ICML 2013)
paper1 paper2 25/04/2014 3:30pm INRIA A103 Julien Mairal

ICCV & NIPS reading sessions

Subject of meeting Materials Date & time Place Speaker
Xiaoyu Wang, Ming Yang, Shenghuo Zhu, Yuanqing Lin
Regionlets for Generic Object Detection
paper slides 11/04/2014 11:30am INRIA A103 Albert Gordo
Tatiana Tommasi, Barbara Caputo
Frustratingly Easy NBNN Domain Adaptation
paper Gabriela Csurka
Pierre Baldi, Peter Sadowski
Understanding Dropout
paper slides Mattis Paulin
Andrea Frome, Greg Corrado, Jon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomas Mikolov
DeViSE: A Deep Visual-Semantic Embedding Model
paper 14/02/2014 3:30pm INRIA A104 Florent Perronnin
João F. Henriques, João Carreira, Rui Caseiro, Jorge Batista
Beyond Hard Negative Mining: Efficient Detector Learning via Block-Circulant Decomposition
paper Adrien Gaidon
Zhenyang Li, Efstratios Gavves, Koen van de Sande, Cees Snoek, Arnold Smeulders
Codemaps Segment, Classify and Search Objects Locally
paper 06/02/2014 11:30am INRIA A104 Danila Potapov
Chenliang Xu, Spencer Whitt, Jason J. Corso
Flattening Supervoxel Hierarchies by the Uniform Entropy Slice
paper slides Yang Hua
Matthew D. Zeiler, Rob Fergus
Visualizing and Understanding Convolutional Networks
paper slides 23/01/2014 12:00pm INRIA A104 Jérôme Revaud
Karen Simonyan, Andrea Vedaldi, Andrew Zisserman
Deep Fisher Networks for Large-Scale Image Classification
paper slides Jakob Verbeek

CVPR & ICML reading sessions

Subject of meeting Materials Date & time Place Speaker
C. Lawrence Zitnick, Devi Parikh
Bringing Semantics Into Focus Using Visual Abstraction
paper slides 04/09/2013 11:00am INRIA A104  Zeynep Akata
Li Wan, Matthew Zeiler, Sixin Zhang, Yann Le Cun, Rob Fergus
Regularization of Neural Networks using DropConnect
paper slides Julien Mairal
Huayan Wang, Daphne Koller
A Fast and Exact Energy Minimization Algorithm for Cycle MRFs
paper slides Anoop Cherian
Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes
Fast Semidifferential-based Submodular Function Optimization
paper slides 21/08/2013 11:00am INRIA A104 Danila Potapov
James Steven Supancic, Deva Ramanan
Self-Paced Learning for Long-Term Tracking
paper slides Yang Hua
Pradipto Das, Chenliang Xu, Richard F. Doell, Jason J. Corso
A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching
paper slides  Dan Oneaţă
Ian Endres, Kevin J. Shih, Johnston Jiaa, Derek Hoiem
Learning Collections of Part Models for Object Recognition
paper slides 17/07/2013 11:00am INRIA A103 Georgia Gkioxari
Sanja Fidler, Roozbeh Mottaghi, Alan Yuille, Raquel Urtasun
Bottom-Up Segmentation for Top-Down Detection
paper slides Gokberk Cinbis
Zhuoyuan Chen, Hailin Jin, Zhe Lin, Scott Cohen, Ying Wu
Large Displacement Optical Flow from Nearest Neighbor Fields
paper slides Heng Wang
Jaechul Kim, Ce Liu, Fei Sha, Kristen Grauman
Deformable Spatial Pyramid Matching for Fast Dense Correspondences
paper slides Jérôme Revaud
Xin Guo, Dong Liu, Brendan Jou, Mojun Zhu, Anni Cai, Shih-Fu Chang
Robust Object Co-detection
paper slides
10/07/2013 11:00am INRIA A103 Mattis Paulin
Thomas Dean, Mark A. Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan, Jay Yagnik
Fast, Accurate Detection of 100,000 Object Classes on a Single Machine
paper slides Naila Murray
Qiang Chen, Zheng Song, Rogerio Feris, Ankur Datta, Liangliang Cao, Zhongyang Huang, Shuicheng Yan
Efficient Maximum Appearance Search for Large-Scale Object Detection
paper slides Albert Gordo
Leonid Pishchulin, Mykhaylo Andriluka, Peter Gehler, Bernt Schiele
Poselet Conditioned Pictorial Structures
paper slides Philippe Weinzaepfel

Sessions in 2013

Subject of meeting Materials Date & time Place Speaker
Tutorial on optimization for sparse estimation slides 18/10/2013 12:00pm INRIA A104 Julien Mairal
Victor Bittorf, Benjamin Recht, Christopher Ré, and Joel A. Tropp
Factoring nonnegative matrices with linear programs
paper  04/06/2013 12:00pm    INRIA C207  Miles Lopes
Mohammad Taha Bahadori, Yan Liu: Granger Causality Analysis in Irregular Time Series. SDM 2012, pp 660-671 paper 21/05/2013 2:00pm    XRCE Mont-Blanc  Boris Chidlovski
Robert E. Schapire
Using output codes to boost multiclass learning problems
paper  06/05/2013 12:00pm  INRIA F107  Mattis Paulin
Richard Socher, Cliff Lin, Andrew Y. Ng and Christopher Manning. I, 2011.
Parsing natural scenes and natural language with recursive neural networks
 [pdf] + [3D Object Classif] + [Word Representations]  19/04/2013 11:00am  XRCE Mont-Blanc  Guillaume Bouchard
Kenneth Lange, David R. Hunter and Ilsoon Yang
Optimization Transfer Using Surrogate Objective Functions
 paper  05/04/2013 11:00am  INRIA A104  Julien Mairal
Kobayashi, T & Otsu, N
Efficient Optimization For Low-Rank Integrated Bilinear Classifiers
 http://bit.ly/12KPa56 [slides]  19/03/2013 2:00pm  XRCE Mont-Blanc  Adrien Gaidon
Daniel Hsu, Sham M. Kakade, and Tong Zhang
A spectral algorithm for learning hidden Markov models
 Hsu et al, 2009
slides other resources
 01/03/2013 11:00am  INRIA A104  Dan Oneaţă
Large-scale distributed deep networks paper slides  19/02/2013 11:00am XRCE Mont-Blanc Cedric Archambeau
Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester and Deva Ramanan
Object Detection with Discriminatively Trained Part Based Models
paper slides  01/02/2013 11:00am  INRIA F107 Philippe Weinzaepfel

Sessions in 2012

Subject of meeting Materials Date & time Place Speaker
Refresher on neural networks and overview of libraries for deep learning. Link to the presentation. Chapter 11 on Neural Networks from The Elements of Statistical Learning 23/11/2012 11:30am     INRIA A104  Adrien Gaidon
Kewei Tu and Vasant Honavar
"Unambiguity Regularization for Unsupervised Learning of Probabilistic Gammars"
paper  09/11/2012 11:00am  XRCE Cour Carree  Dr. James Henderson
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Nicolas Chesneau,
Apr 6, 2015, 3:23 AM
ć
Nicolas Chesneau,
May 19, 2015, 7:42 AM
Ċ
Nicolas Chesneau,
May 19, 2015, 7:40 AM
Ċ
Dan Oneata,
Jul 17, 2013, 4:55 AM
Ċ
Dan Oneata,
Sep 11, 2013, 8:50 AM
Ċ
Dan Oneata,
Jan 22, 2014, 6:45 AM
ć
Dan Oneata,
Jan 23, 2014, 1:55 AM
ć
Dan Oneata,
Jul 17, 2013, 1:36 AM
Ċ
demo.pdf
(1459k)
Nicolas Chesneau,
Apr 2, 2015, 8:55 AM
Ċ
Dan Oneata,
Sep 11, 2013, 8:50 AM
Ċ
Dan Oneata,
Jul 11, 2013, 5:19 AM
Ċ
Dan Oneata,
Jul 11, 2013, 5:12 AM
Ċ
Dan Oneata,
Apr 15, 2014, 2:22 AM
Ċ
Guillaume Bouchard,
Feb 19, 2013, 5:57 AM
Ċ
Dan Oneata,
Jul 11, 2013, 7:01 AM
Ċ
Nicolas Chesneau,
Apr 2, 2015, 9:05 AM
Ċ
Dan Oneata,
Apr 15, 2014, 2:22 AM
Ċ
Dan Oneata,
Jul 11, 2013, 7:27 AM
Ċ
Dan Oneata,
Aug 22, 2013, 2:07 AM
ć
Dan Oneata,
Sep 11, 2013, 8:50 AM
Ċ
slides.pdf
(5427k)
Nicolas Chesneau,
Apr 2, 2015, 8:55 AM
Ċ
Dan Oneata,
Aug 22, 2013, 2:07 AM
Ċ
Dan Oneata,
Apr 15, 2014, 2:23 AM
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