The conference paper describing the dataset and the course of the competition can be cited by (BibTeX):

@inproceedings{Houben-IJCNN-2013,
   author = {Sebastian Houben and Johannes Stallkamp and Jan Salmen and Marc Schlipsing and Christian Igel},
   booktitle = {International Joint Conference on Neural Networks},
   title = {Detection of Traffic Signs in Real-World Images: The {G}erman {T}raffic {S}ign {D}etection {B}enchmark},
   number = {1288},
   year = {2013},
}

Our special session at the annual IJCNN was very well-attended. We want to thank the presenters for their interesting and fitting talks and the participants for the vivid disucssion afterwards.

(Xiaolin Hu (Teams wff and LITS1), Alioscia Petrelli (Team BolognaCVLab), Markus Matthias (Team VISICS), Sebastian Houben (Organizer), Alberto De Souza (Team lcad-ufes)

We put together the test and training dataset with full annotations for download. Please refer to the 'Dataset' section for the links.

To our information the submission system will be online until at least March 8, 2013, possibly longer. For those of you are late with their results or intended to write a paper but were to pressed for time this should be an ideal opportunity.

Due to anew (and unannounced) changes in IJCNN submission schedule, we decided to reopen the submission site. You will be able to submit results again and they will be displayed in the "Results" section as before. However, for fairness reasons you will not be able to compete for the competition prizes.

Please note the submission instructions below when submitting, as resubmission will not be possible.

Please do also contact us if you have further questions.

Dear teams,

the submission is closed. Thank you for participating in the German Traffic Sign Detection Benchmark. You can now see the final results evaluated on the entire test dataset in section "Results". In particular, we want to congratulate the teams

wgy@HIT501 (Prohibitive, Mandatory)

visics (Prohibitive, Danger)

LITS1 (Prohibitive)

who managed to achieve perfect results in a category.

To this time, the submission deadline of the IJCNN has not been extended and it is still uncertain whether it will be. Please do not forget to hand in your papers if you planned to do so. Please do also follow the submission instructions below.

Dear participants,

we added some details to the "Results" section that might be useful if you are writing a paper. Please log into your account and open the site "Results". Below the ranking you will find the precision-recall pairs of your own submissions in case you want to use them in a plot.

As a tie breaker we also introduced the average overlap of your true positive detections.

We (again) will have to revise the final date of the submission phase, since another deadline extension for the IJCNN 2013 is under discussion. If the deadline is postponed, we will accordingly adjust the end of the submission phase. However, teams that prepare a paper should be prepared to hand in their papers on the upcoming Friday.

As we discussed with several teams before, we cordially invite all participants to submit a paper on their respective algorithms to the IJCNN 2013. You will find the necessary information at http://www.ijcnn2013.org/paper-submission.php . On the submission form please select the Main Research Topic 'C02. German Traffic Sign Detection Competition' (under Cross-Disciplinary Topics) to make sure that your papers can be related to this competition.

Please pay attention to the firm deadline on Friday, March 1, 2013. We will close the competition on Friday at 8 am CET. At that point you will be able to see your results evaluated on the whole evaluation dataset (Section 'Results'). Logging into your account will make sure the precision-recall plots of your submissions are shown in the section 'Results'.

When you refer to the competition, please cite the following paper (BibTeX):

@inproceedings{Houben-IJCNN-2013,
author = {Sebastian Houben and Johannes Stallkamp and Jan Salmen and Marc Schlipsing and Christian Igel},
booktitle = {International Joint Conference on Neural Networks (submitted)},
title = {Detection of Traffic Signs in Real-World Images: The {G}erman {T}raffic {S}ign {D}etection {B}enchmark},
year = {2013},
}

@inproceedings{Houben-IJCNN-2013,
   author = {Sebastian Houben and Johannes Stallkamp and Jan Salmen and Marc Schlipsing and Christian Igel},
   booktitle = {International Joint Conference on Neural Networks},
   title = {Detection of Traffic Signs in Real-World Images: The {G}erman {T}raffic {S}ign {D}etection {B}enchmark},
   number = {1288},
   year = {2013},
}

By popular demand we have raised the submission limit to 10 submissions per team.

Dear participants in the IJCNN-2013-Traffic-Sign-Detection-Benchmark,

the submission phase is officially started. Please download the test dataset from section "Dataset", process it with your algorithm of choice, and submit your result file by means of the new section "Submission".

As we described in detail in the section "Dataset", you can (and should) assemble several result files with the specified format of several of your algorithm's runs with possibly different parametrization in a single zip file.
The result text files within are parsed on our server and the result is immediatly visible to you and all other participants.

Please note that the shown results are preliminary. The performance is evaluated on a subset of the whole test dataset for the time being. The final performance will be shown after the submission phase is over, which will be shorty before the IJCNN's paper submission deadline. By revealing the final performance to a later point of time we hope to prevent teams from overfitting their parametrizations to the data.

Please feel free to contact us with whatever questions or problems might occur during the competition.

Good luck!

After the IJCNN has officially announced our competition we decided to start the submission phase on Monday, February 18, 2013, at 10 am CET. The submission site will continue to stay open until shortly before the IJCNN's paper submission deadline.

After checking with the IJCNN's competition organizer, we decided to postpone the announced submission phase to most likely the first weeks of February. We will provide you with a definite date as soon as possible.

It is very likely that the current submission deadline (22 February, 2013) will be extended. We will take care that you will have enough time to prepare your papers after the competition. It will also be possible to hand in preliminary results.

We are sorry to inform you on such short notice, but in order to attract as many teams as possible we want to align with the IJCNN's schedule.

Thanks to several remarks from participating teams we have updated the ground truth of the training dataset. You can download the data package or the ground truth text file only. If you decide for the latter, please consider that the submission example file (ex.txt) and the image section subdirectories (00 - 42) have changed, too.

We added 6 further ground truth entries. 4 of the corresponding signs are at the limit of the minimal size of 16x16 pixels. 2 were well-hidden. Furthermore a class ID was incorrectly annotated. Therefore one sign of a non-relevant category changes to "mandatory".

Some teams aproached us with wishes for the date of the postponed submission phase. For example, the Chinese New Year holiday season is just around the corner. If you have problems with the submission being held in February, please let us know.

The submission site will be opened on Wednesday, 23 January, 2013, at 10 am CET.

We are currently discussing the schedule with the IJCNN organizers.

Due to delays in the review process of the IJCNN we decided to adapt the schedule of our submission phase. It will begin on January 23, 2013, as planned, but
will stay opened longer than previously announced. The final date is yet unclear, but we want to give a fair chance to teams that will be attracted by the IJCNN competition announcements.

The IJCNN paper submission deadline has been extended to February 22, 2013. This should allow all teams working on papers to finish in time with first results.

Unfortunately, the ReadMe.txt in the download package with the GTSDB training data (TrainIJCNN2013.zip) contains an error. Two class IDs have mistakenly been added to the prohibitive and the danger traffic sign category. The download package has been corrected, the correct categories are

  prohibitory = [0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 15, 16] (circular, white ground with red border)
  mandatory = [33, 34, 35, 36, 37, 38, 39, 40] (circular, blue ground)
  danger = [11, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31] (triangular, white ground with red border)
 
Teams that used our C++ or Matlab function library will find the correct categories in the respective subroutines. This mistake only concerned the ReadMe.txt in the download package.
 
We thank the team that pointed this out to us and apologize for the inconvenience.

For your motivation we uploaded results from three different baseline detectors that are popular in the literature: a Viola-Jones detector based on Haar features, a Hough-like voting scheme that detects circles and triangles, and a LDA based on HOG features that is used as a detector by presenting it all possible image sections.

Refer to the new section "Results" for an overview.

You can now download code snippets in the section "Dataset" that facilitate your work with the training dataset. There are downloads for C++ and Matlab. Both packages contain functions to read ground truth data from the training dataset, to test and evaluate your self-implemented detector functions by presenting the downloaded images one by one, and to evaluate a text file that contains the results of your detector in the format you would need to submit during the competition.

Feel free to contact us with whatever questions you might have,

By popular demand we are glad to announce the German Traffic Sign Detection Benchmark (GTSDB) as a successor to the German Traffic Sign Recognition Benchmark.
Research teams with background in image processing and / or machine learning are cordially invited to compete with their algorithms in this new challenge.
For details, downloads, and regulations feel free to browse the sections About and Dataset.

The notification of acceptance for our benchmark proposal at the IEEE International Joint Conference for Neural Networks (IJCNN) 2013 will be put out on December 19th, 2012.