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Google at CVPR 2017
Friday, July 21, 2017
Posted by Christian Howard, Editor-in-Chief, Research Communications
From July 21-26, Honolulu, Hawaii hosts the
2017 Conference on Computer Vision and Pattern Recognition
(CVPR 2017), the premier annual computer vision event comprising the main conference and several co-located workshops and tutorials. As a leader in computer vision research and a Platinum Sponsor, Google will have a strong presence at CVPR 2017 — over 250 Googlers will be in attendance to present papers and invited talks at the conference, and to organize and participate in multiple workshops.
If you are attending CVPR this year, please stop by our booth and chat with our researchers who are actively pursuing the next generation of intelligent systems that utilize the latest machine learning techniques applied to various areas of
machine perception
. Our researchers will also be available to talk about and demo several recent efforts, including the technology behind
Headset Removal for Virtual and Mixed Reality
,
Image Compression with Neural Networks
,
Jump
,
TensorFlow Object Detection API
and much more.
You can learn more about our research being presented at CVPR 2017 in the list below (Googlers highlighted in blue).
Organizing Committee
Corporate Relations Chair -
Mei Han
Area Chairs include -
Alexander Toshev
,
Ce Liu
,
Vittorio Ferrari
,
David Lowe
Papers
Training object class detectors with click supervision
Dim Papadopoulos,
Jasper Uijlings
, Frank Keller,
Vittorio Ferrari
Unsupervised Pixel-Level Domain Adaptation With Generative Adversarial Networks
Konstantinos Bousmalis
,
Nathan Silberman
,
David Dohan
,
Dumitru Erhan
,
Dilip Krishnan
BranchOut: Regularization for Online Ensemble Tracking With Convolutional Neural Networks
Bohyung Han,
Jack Sim
,
Hartwig Adam
Enhancing Video Summarization via Vision-Language Embedding
Bryan A. Plummer,
Matthew Brown
, Svetlana Lazebnik
Learning by Association — A Versatile Semi-Supervised Training Method for Neural Networks
Philip Haeusser,
Alexander Mordvintsev
, Daniel Cremers
Context-Aware Captions From Context-Agnostic Supervision
Ramakrishna Vedantam,
Samy Bengio
,
Kevin Murphy
, Devi Parikh,
Gal Chechik
Spatially Adaptive Computation Time for Residual Networks
Michael Figurnov,
Maxwell D. Collins
,
Yukun Zhu
,
Li Zhang
,
Jonathan Huang
,
Dmitry Vetrov, Ruslan Salakhutdinov
Xception: Deep Learning With Depthwise Separable Convolutions
François Chollet
Deep Metric Learning via Facility Location
Hyun Oh Song
, Stefanie Jegelka,
Vivek Rathod
,
Kevin Murphy
Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors
Jonathan Huang
,
Vivek Rathod
,
Chen Sun
,
Menglong Zhu
,
Anoop Korattikara
,
Alireza Fathi
,
Ian Fischer
,
Zbigniew Wojna
,
Yang Song
,
Sergio Guadarrama
,
Kevin Murphy
Synthesizing Normalized Faces From Facial Identity Features
Forrester Cole
, David Belanger,
Dilip Krishnan
,
Aaron Sarna
,
Inbar Mosseri
,
William T. Freeman
Towards Accurate Multi-Person Pose Estimation in the Wild
George Papandreou
,
Tyler Zhu
,
Nori Kanazawa
,
Alexander Toshev
,
Jonathan Tompson
,
Chris Bregler
,
Kevin Murphy
GuessWhat?! Visual Object Discovery Through Multi-Modal Dialogue
Harm de Vries, Florian Strub, Sarath Chandar,
Olivier Pietquin
, Hugo Larochelle, Aaron Courville
Learning discriminative and transformation covariant local feature detectors
Xu Zhang,
Felix X. Yu
, Svebor Karaman, Shih-Fu Chang
Full Resolution Image Compression With Recurrent Neural Networks
George Toderici
,
Damien Vincent
,
Nick Johnston
,
Sung Jin Hwang
,
David Minnen
,
Joel Shor
,
Michele Covell
Learning From Noisy Large-Scale Datasets With Minimal Supervision
Andreas Veit,
Neil Alldrin, Gal Chechik, Ivan Krasin
, Abhinav Gupta, Serge Belongie
Unsupervised Learning of Depth and Ego-Motion From Video
Tinghui Zhou,
Matthew Brown
,
Noah Snavely
,
David G. Lowe
Cognitive Mapping and Planning for Visual Navigation
Saurabh Gupta,
James Davidson
,
Sergey Levine
,
Rahul Sukthankar
, Jitendra Malik
Fast Fourier Color Constancy
Jonathan T. Barron
,
Yun-Ta Tsai
On the Effectiveness of Visible Watermarks
Tali Dekel,
Michael Rubinstein
,
Ce Liu
,
William T. Freeman
YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video
Esteban Real
,
Jonathon Shlens
,
Stefano Mazzocchi
,
Xin Pan
,
Vincent Vanhoucke
Workshops
Deep Learning for Robotic Vision
Organizers include:
Anelia Angelova
,
Kevin Murphy
Program Committee includes:
George Papandreou
,
Nathan Silberman
,
Pierre Sermanet
The Fourth Workshop on Fine-Grained Visual Categorization
Organizers include:
Yang Song
Advisory Panel includes:
Hartwig Adam
Program Committee includes:
Anelia Angelova
,
Yuning Chai
,
Nathan Frey
,
Jonathan Krause
,
Catherine Wah
,
Weijun Wang
Language and Vision Workshop
Organizers include:
R. Sukthankar
The First Workshop on Negative Results in Computer Vision
Organizers include:
R. Sukthankar
,
W. Freeman
,
J. Malik
Visual Understanding by Learning from Web Data
General Chairs include:
Jesse Berent
,
Abhinav Gupta
,
Rahul Sukthankar
Program Chairs include:
Wei Li
YouTube-8M Large-Scale Video Understanding Challenge
General Chairs:
Paul Natsev, Rahul Sukthankar
Program Chairs:
Joonseok Lee, George Toderici
Challenge Organizers:
Sami Abu-El-Haija
,
Anja Hauth
,
Nisarg Kothari
,
Hanhan Li
,
Sobhan Naderi Parizi
,
Balakrishnan Varadarajan
,
Sudheendra Vijayanarasimhan
,
Jian Wang
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