Workshop Paper Submission
Submission Site: https://cmt3.research.microsoft.com/AIC2020/
Deadline: Monday, April 13 (09:00 AM, Pacific Time)
All participating teams are invited to submit original papers on subject topics in Intelligent Transportation System (ITS) to the 4th AI City Challenge Workshop at CVPR 2020. For teams willing to compete for challenge awards (winners or runners-up), each of them is required to submit at least one paper to the workshop. Our review will be based on algorithmic innovation and the quality of the description. Each paper can be up to 8 pages, excluding references, with an additional 2 pages for references. Please use the LaTex/Word template from CVPR 2020. The final version, instead of the version for review, should be used, because the review process is NOT double-blind. For teams participating in multiple tracks, they are allowed to submit more than one paper, but the content of the papers should not have significant overlap, e.g., repeating the same description about an algorithmic design used in both Track 2 and Track 3. All the accepted papers will be officially published by IEEE Xplore and CVF Open Access as CVPR 2020 workshop papers and will be freely accessible online and indexed by Google Scholar, ResearchGate, CNKI, etc.
Since we only have a short review period and there are only about 24 hours for editing accepted papers for camera-ready submission, the submitted workshop papers are expected to be of high quality, ready for publication. We suggest the participating teams to start drafting their papers as early as possible, and leave only the experimental comparison by the challenge deadline. The teams could add their results when the final leaderboard is released.
We request all submissions to avoid using the term “surveillance” in their papers, as our datasets are mainly designed for the analysis and prediction of traffic flow for applications in smart cities. Surveillance-related papers are suggested to be submitted to the International Conference on Advanced Video and Signal-based Surveillance (AVSS).