Papers
The ApolloScape Dataset for Autonomous Driving
Xinyu Huang*, Baidu; Xinjing Cheng, Baidu; Qichuan Geng, Baidu; Binbin Cao, Baidu; Dingfu Zhou, Baidu; Peng Wang, Baidu USA LLC; Yuanqing Lin, Baidu; Yang Ruigang, Baidu
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System
Jeongyeol Baek*, LG Electronics; Ioana Veronica Chelu, Arnia; Livia Iordache, Arnia; Vlad Paunescu, Arnia; HyunJoo Ryu, LG Electronics; Alexandru Ghiuta, Arnia; Andrei Petreanu, Arnia; Yunsung Soh, LG Electronics; Andrei Leica, Arnia; ByeongMoon Jeon, LG Electronics
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain RandomizationTraining Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization
Jonathan Tremblay*, Nvidia; Aayush Prakash, Nvidia; David Acuna, Nvidia; Mark Brophy, Nvidia; Varun Jampani, Nvidia Research; Cem Anil, Nvidia; Thang To, Nvidia; Eric Cameracci, Nvidia; Shaad Boonchoon, Nvidia; Stan Birchfield, NVIDIA
On the iterative refinement of densely connected representation levels for semantic segmentation
Arantxa Casanova*, MILA; Guillem Cucurull, Computer Vision Center; Michal Drozdzal, Facebook; Adriana Romero, FAIR; Yoshua Bengio, Universite de Montreal
Minimizing Supervision for Free-space Segmentation
Satoshi Tsutsui, Indiana University; Tommi Kerola*, Preferred Networks, Inc.; Shunta Saito, Preferred Networks, Inc.; David Crandall, Indiana University
Error Correction for Dense Semantic Image Labeling
Yu-Hui Huang*, KU Leuven; Xu Jia, KU Leuven; Stamatios Georgoulis, ETH Zurich; Tinne Tuytelaars, K.U. Leuven; Luc Van Gool, ETH Zurich
On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach
Nikolai Smolyanskiy, NVIDIA; Alexey Kamenev, NVIDIA; Stan Birchfield*, NVIDIA
Accurate Deep Direct Geo-Localization from Ground Imagery and Phone-Grade GPS
Shaohui Sun*, Lyft; Ramesh Sarukkai, Lyft; Jack Kwok, Lyft; Vinay Shet, Lyft
Efficient and Safe Vehicle Navigation Based on Driver Behavior Classification
Chor Hei Ernest Cheung*, The University of North Carolina at Chapel Hill; Aniket Bera, The University of North Carolina at Chapel Hill; Dinesh Manocha, University of North Carolina
Detection of Distracted Driver using Convolutional Neural Network
Bhakti Baheti*, SGGSIE&T, Nanded, MH; Suhas Gajre, S.G.G.S. Nanded; Sanjay Talbar, SGGSIET Nanded
The ApolloScape Dataset for Autonomous Driving
Xinyu Huang*, Baidu; Xinjing Cheng, Baidu; Qichuan Geng, Baidu; Binbin Cao, Baidu; Dingfu Zhou, Baidu; Peng Wang, Baidu USA LLC; Yuanqing Lin, Baidu; Yang Ruigang, Baidu
Classifying Group Emotions for Socially-Aware Autonomous Vehicle Navigation
Aniket Bera*, The University of North Carolina at Chapel Hill; Tanmay Randhavane, The University of North Carolina at Chapel Hill; Emily Kubin, The University of North Carolina at Chapel Hill; Austin Wang, The University of North Carolina at Chapel Hill; Kurt Gray, The University of North Carolina at Chapel Hill; Dinesh Manocha, University of North Carolina
AutonoVi-Sim: Autonomous Vehicle Simulation Platform with Weather, Sensing, and Traffic Control
Andrew Best*, UNC Chapel Hill; Sahil Narang, UNC Chapel Hill; Lucas Pasqualin, University of Central Florida; Daniel Barber, University of Central Florida; Dinesh Manocha, University of North Carolina
Learning Hierarchical Models for Class-Specific Reconstruction from Natural Data
Arun CS Kumar*, University of Georgia; Suchendra Bhandarkar, University of Georgia; Mukta Prasad, Trinity College, Dublin
Subset Replay based Continual Learning for Scalable Improvement of Autonomous Systems
Pratik Brahma*, Volkswagen Electronics Research Lab; Adrienne Othon, Volkswagen Electronics Research Lab
Important Dates

· Paper submission deadline: 27th March 2018

· Notification to authors: 10th April 2018

· Camera ready deadline: 20th April 2018

Submission Procedure

we solicit submissions in the following areas:

· Autonomous navigation and exploration

· Vision-based advanced driver assistance systems

· Vision-based underwater and unmanned aerial vehicles

· Visual driver monitoring and driver-vehicle interfaces

· On-board camera calibration

· Performance evaluation of vehicular applications

· Machine learning techniques for vehicle technology

· Vision based geo-localization

We will have additional one or two panel session for discussion potential issues and future directions for autonomous driving.


Authors should take into account the following:

The submission site is https://cmt3.research.microsoft.com/WAD2018

The maximum paper length is 8 pages (plus references). The format of the papers is the same as the CVPR main conference.We accept dual submissions to CVPR 2018 and WAD 2018, but the manuscript must contain substantial original contents not submitted to any other conference, workshop or journal.

Submissions will be rejected without review if they:

· contain more than 8 pages (excluding references)

· violate the double-blind policy or violate the dual-submission policy

Manuscript templates can be found at the main conference website: http://cvpr2018.thecvf.com/submission