2017

The 13th IEEE Embedded Computer Vision Workshop

evw2017-logo

 

July 21, 2017,
Honolulu, HI, USA

Held in conjunction with IEEE CVPR 2017.

Main theme: Autonomous Driving

 

 

Best paper from Embedded Vision Workshop  2017:

Bichen Wu, Forrest Iandola, Peter Jin, Kurt Keutzer, SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

cof

Program

Each oral presentation includes a 15 minute talk followed by 5 minute Q&A session. Poster presentations include 2-minute spotlight followed by the poster presentation during the allocated time. The poster dimensions are 4×8 (maximum).

Location:
Schedule: Full day

Session Start Time Paper/Talk Title Author/Speaker
0800 Welcome
S1: Oral 1 (0810-1000) 0810 Invited/Keynote Talk: Deep Learning for Autonomous Driving Branislav Kisacanin, Nvidia
0900 Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots Chen Zhou; Jiaolong Yang; Chunshui Zhao; Gang Hua
0920 Sparse, Quantized, Full Frame CNN for Low Power Embedded Devices Manu Mathew; Kumar Desappan; Pramod Swami; Soyeb Nagori
0940 Reconstructing Intensity Images from Binary Spatial Gradient Cameras Suren Jayasuriya; Orazio Gallo; Jinwei Gu; Timo Aila; Kautz Jan
1000 Morning Break
S2: Oral 2 (1030-1230) 1030 Invited/Keynote Talk: Computer Vision for Camera Drones Friedrich Fraundorfer, Graz University of Technology (TU Graz)
1120 Binarized Neural Network with Separable Filters Jeng-Hau Lin; Tianwei Xing; Ritchie Zhao; Zhiru Zhang; Mani Srivastava; Zhuowen Tu; Rajesh Gupta
1140 Joint Mobile-Cloud Video Stabilization Gbolahan S Adesoye; Oliver Wang
1200 Embedded Robust Visual Obstacle Detection on Autonomous Lawn Mowers Mathias Franzius; Mark Dunn; Roman Dirnberger; Nils Einecke
1230 Lunch
S3: Poster 1 (1330-1540) 1330 Invited/Keynote Talk: Bootstrapping AI from naturalistic driving Stefan Heck, Nauto (CEO)
1420 Spotlights Posters and Demos
1440 Posters
Improved Cooperative Stereo Matching for Dynamic Vision Sensors with Ground Truth Evaluation Ewa Piatkowska; Jürgen Kogler; Nabil Belbachir; Margrit Gelautz
Diagnostic mechanism and robustness of safety relevant automotive deep convolutional networks Robert Krutsch; Rolf Schlagenhaft
Hand gesture based Region marking for tele-support using wearables Archie Gupta; Shreyash Mohatta; Jitender Maurya; Ramakrishna Perla; Ramya Hebbalaguppe; Ehtesham Hassan
Even More Confident predictions with deep machine-learning Matteo Poggi; Fabio Tosi; Stefano Mattoccia
Low-complexity Global Motion Estimation for Aerial Vehicles Nirmala Ramakrishnan; Alok Prakash; Srikanthan Thambipilla
LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection for Embedded Systems Subarna Tripathi; Gokce Dane; Byeongkeun Kang; Vasudev Bhaskaran; Truong Nguyen
Image-based Visual Perception and Representation for Collision Avoidance Cevahir Cigla; Roland Brockers; Larry Matthies
Pruning ConvNets Online for Efficient Specialist Models Jia Guo; Miodrag Potkonjak
Real-time Driver Drowsiness Detection for Embedded System Using Model Compression of Deep Neural Networks Bhargava Reddy Thipireddy; Kim Yehoon; Sojung Yun; Chanwon Seo; Junik Jang
1540 Afternoon Break
S4: Oral 3 (1600-1700) 1600 SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving Bichen Wu; Forrest Iandola; Peter Jin; Kurt Keutzer
1620 Training Sparse Neural Networks Suraj Srinivas; Akshayvarun Subramanya; Venkatesh Babu R.
1640 SqueezeMap: Fast Pedestrian Detection on a Low-power Automotive Processor Using Efficient​ Convolutional Neural Networks Rytis Verbickas; Robert Laganiere; Daniel Laroche; Changyun Zhu; Xiaoyin Xu; Ali Ors
1700 Closing Remarks and Awards

Sponsors

NVIDIA Corporation kindly sponsors this year’s best paper award!
nvidia

Call For Papers

Embedded Vision is what makes Computer Vision mainstream today, as it brings together embedded systems with vision functionalities. Due to the emergence of powerful yet low-cost and energy-efficient processors, it has become possible to incorporate vision capabilities into a wide range of embedded systems, including video search and annotation, surveillance, gesture recognition in video games, driver assist systems in automotive safety, and autonomous robots such as drones. The IEEE Embedded Vision Workshop (EVW) brings together researchers working on vision problems that share embedded system characteristics.

CFP: https://drive.google.com/file/d/0B-aYI7rgXZ2vVzZrMXF4emxsVlk/view?usp=sharing

Important Dates

  • Paper submission: March 31, 2017
  • Notification to the authors: May 12, 2017
  • Camera ready paper: May 19, 2017

Paper submission: http://cmt3.research.microsoft.com/EVW2017

Author guidelines: http://cvpr2017.thecvf.com/submission/main_conference/author_guidelines

Demos

EVW will have live demonstrations of embedded vision prototypes and solutions. This year we strongly encourage authors to embed their demo into their talk. We will provide 5 extra minutes in order to have enough time for the demo.

Furthermore we plan a demo session during which authors, engineers, and researchers can showcase their prototypes with real-time implementations of vision systems on embedded computing platforms. Additionally, we invite abstracts, independent of the paper submissions, to present your demonstrations during the workshop.

Special Journal Issue on Embedded Computer Vision

Since 2005 Workshops on Embedded (Computer) Vision (ECVW and EVW) were held in conjunction with CVPR, with the exception of the fifth, which was held in conjunction with ICCV 2009. These events were very successful, and selected workshop papers have been published in several special issues of major journals (EURASIP Journal on Embedded Systems, CVIU and Springer monographs titled Embedded Computer Vision). This year, we also plan to organize a special issue for selected papers.

Organizing Committee

General Chair:

Martin Humenberger, AIT Austrian Institute of Technology
Swarup Medasani, Uurmi Systems

Program Chair:

Ravi Kumar Satzoda, Nauto Inc.
Zoran Nikolic, Nvidia

Sponsorship Chair:

Goksel Dedeoglu, PercepTonic

Steering Committee:

Stefano Mattoccia, University of Bologna, Italy
Jagadeesh Sankaran, Nvidia
Ahmed Nabil Belbachir, Teknova AS (Norway)
Sek Chai, SRI International
Margrit Gelautz, Vienna University of Technology
Branislav Kisacanin, Nvidia
Fridtjof Stein, Daimler AG

Web Chair:

Yu Wang, Ambarella

 

Program Committee (tentative):

Abelardo Lopez-Lagunas, ITESM
Antonio Haro, Navteq
Bernhard Rinner, Klagenfurt University
Burak Ozer, Verificon
David Ilstrup, Honda Research Institute
David Moloney, Movidius
Dipan Mandal, Intel Corporation
Hassan Rabah, University of Lorraine
Hongying Meng, Brunel University
Khanh Duc, Nvidia
Kofi Appiah, Nottingham Trent University
Linda Wills, Georgia Tech
Marilyn Wolf, Georgia Tech
Peter Venetianer, Digital Signa Corp.
Rajesh Narasimha, MetaIO
Sebastiano Battiato, U.of Catania
Steve Mann, University of Toronto
Sven Fleck, SmartSurv
Terry Boult, U.of Colorado
Vinay Sharma, Apple
Vittorio Murino, Istituto Ital.di Tecn.
Zhu Li, Hong Kong Polytechnic University
Senyo Apewokin, Texas Instruments
Moshe Ben-Ezra, Microsoft
Faycal Bensaali, Qatar University
Xin Chen, Naivety
Rita Cucchiara, U. of Modena and Reggio Emilia
Orazio Gallo, Nvidia
Masatoshi Ishikawa, U. of Tokyo
Kihwan Kim, Nvidia
Kevin Koeser, ETH Zurich
Zhu Li, Hong Kong Polytechnic U.
Darnell Moore, Texas Instruments
Andre Morin, Lyrtech
Zoran Zivkovic, NXP
Sankalita Saha, NASA
Mainak Sen, Cisco Systems
Dabral Shashank, Texas Instruments
Salvatore Vitabile, U.of Palermo
Ruigang Yang, U. of Kentucky
Witek Jachimczyk, Mathworks
Zoran Zivkovic, Intel Corporation
Stephan Weiss, Klagenfurt University
Roland Brockers, JPL
Thomas Kadiofsky, AIT Austrian Institute of Technology
Markus Murschitz, AIT Austrian Institute of Technology
Daniel Steininger, AIT Austrian Institute of Technology
Nicolas Thorstensen, IVISO GMBH
Florian Seitner, emotion3D GmbH
Tse-Wei Chen, Canon Inc.

Advertisements
This entry was posted in Past Embedded Vision Workshops. Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s