news

9/27 Documents of online seminar to explain the reference implementation was released in the tutorial.
9/21 We will change the recommended board to SK-KV260-G-ED and SK-KV260-G.
9/16 A reference environment (software) using the distributed data of this contest has been released in the tutorial.
9/13 We have started accepting online seminars (9/27). If you would like to participate, please register here.
9/8 We have started accepting board provision review (1st round). If you are interested, please apply from here.
9/2 We are considering changing the recommended boards to SK-KV260-G-ED and SK-KV260-G. Board provision review will be implemented in stages, and the first is scheduled for the end of September.
8/31 The reference environment (software) was released in the tutorial.

Purpose
With the progress of artificial intelligence (AI) technology, social implementation such as image recognition using AI technology, automatic driving, and natural language processing is rapidly progressing. Especially in the edge computing field, since it is necessary to realize AI technology with higher efficiency, startups mainly in the United States and China and major vendors are accelerating their entry into AI hardware, and even in Japan Not only that, there is an urgent need to develop human resources and industries for hardware to accelerate AI processing such as LSI and FPGA.

In addition, it is seen the recent growing oligopolistic in embedded processors with the rigidity of prices as a challenge.

Given this background, under the theme of "RISC-V" which is open source and does not require licensing fees, this contest sets the task of developing a system including hardware and software (network model and system optimization) equipped with RISC-V chips, in addition to the conventional AI technology development focusing on software, and is designed to develop human resources and startups with AI hardware in mind, as well as to foster industries that utilize these technologies.

In this contest, we will provide a reference environment for software and hardware as well as various types of support. We hope that you will use them as a starting point for your challenge in the field of edge computing.

AI Edge Contest Official Website
Special Website for the 6th AI Edge Contest


Contest Outline

Subject (Algorithm development) Create an algorithm for 3D object detection from images and LIDAR data of a vehicle front camera
(Algorithm implementation) Design hardware accelerators and implement algorithm on the target platform equipped with RISC-V.
Provided data Images of a vehicle front camera
Lider data of a vehicle front camera
Labeled 3D bounding boxes and categories of objects
Identifying target Car, Pedestrian
Implementation Using RISC-V in the processing of object tracking
Platform Any FPGA board and boards with RISC-V in addition to the Ultra96 board
Final result set Source code, area report, implementation approach, processing performance, etc.
Evaluation Evaluated by reviews for overall points for completeness (qualitative), accuracy (quantitative), and speed of operation (quantitative)
Prize. Outstanding Performance Award: 
1st Prize: 1,000,000 yen + Google Cloud Platform Coupon (200,000 yen)
 + Sakura Cloud Coupon (200,000 yen), Trophy
2nd Prize: 600,000 yen + Google Cloud Platform Coupon (10,000 yen) + Sakura Cloud Coupon (100,000 yen), Trophy
3rd Prize: 300,000 yen + Google Cloud Platform Coupon (50,000 yen) + Sakura Cloud Coupon (50,000 yen), Trophy
Special Jury Prize 300,000 yen + Google Cloud Platform Coupon (50,000 yen) + Sakura cloud Coupon (50,000 yen), Trophy
Web Article Prize: Share total 40,000 yen Amazon gift card among Web Article Winners (up to 10 teams)
* If there is no post or article that corresponds to the prize, it will be "None".



Subject 

You are required to create an algorithm for object detection using a 3D bounding box on image data and point cloud data acquired by a sensor mounted on a vehicle.
The objects to be detected are as follows.

  • Pedestrian: Within 40[m] of the vehicle and containing at least one point cloud
  • Car: Within 50[m] of the vehicle and containing at least one point group

The 3D bounding box is represented by the (x, y) coordinates of its center in the world coordinate system.


Please also refer to the distribution data (readme.md).


Subject (Algorithm Implementation)

Implement the developed algorithm on the target platform equipped with a RISC-V chip.

The section to be optimized and the processing time to be measured is defined as follows.
Time to perform inference processing on the video data loaded in the memory and then convert it to JSON-equivalent information such as the label and 3D bounding box information of each object.

Carefully check the RISC-V usage requirements described in the "Rules" tab before implementing.


Flow of entry

  1. Download data from the Data tab and develop the algorithm required in the subject (algorithm development)
    ・It is not necessary to use both image data and LIDAR data. For example, it is acceptable to use both types of data for training and only use image data for inference.
    ・Please include in the report any points of appeal such as what you put a lot you think into.
  2. Submit source code for developed algorithms
    ・When you post your inference results from the "Submit" button, you can see the evaluation results (accuracy and inference time) on the leaderboard.
    ・Leaderboard ratings are not used for the final evaluation. Please use them as a reference.
    ・Until the end of the contest, you may submit as many times as you like, within the maximum number of times per day.
  3. Implement and optimize the developed algorithm on the environment required by the subject (algorithm Implementation)
    ・For those who do not have FPGA boards, we plan to offer them after reviewing the status of the initiative.
       Application form is here.
     * The screening process will also take into account the results of algorithmic submissions.
    ・Repeat Steps 2 and 3 to optimize.
  4. Submit final submissions by the end of the contest (see "submission_details.pdf")
    ・Please upload the file to Dropbox, GigaFile, or other online service and submit the necessary information for downloading. (Submission form will be available as soon as it is ready.)
     * Please make sure the SD card size is 32GB or less.
    ・Please agree to grant an open source license to your submission.


Slack workspace
We have prepared a dedicated Slack workspace for the AI ​​edge contest, so please participate. In addition to information exchange and discussion among participants, it is also possible to use it for recruiting team members and to communicate with sponsoring companies. (link in data tab)

Decision Procedure of Winners

The winners will be selected from those who meet the requirements after the final submissions are reviewed by the organizer's office. In addition, an online interview will be set up to provide a presentation on implementation ideas, etc. (5-minute presentation + 10-minute Q&A session is expected).

Requirements

  • Submit final submissions by the end of the contest and complete all required submissions
  • Agree to grant an open source license to your submission
  • Fulfill the rules
  • he processing performance measurement application should work and the results should be displayed in a file and/or on a console.
  • *Reports are not required, but we recommend submitting even a brief description to help narrow down the points for review.

Criteria for Judgment

The following three items will be scored by the contest judges, and the overall score will determine the ranking. Each item will be evaluated equally, but the Special Jury Prize will focus on the degree of completion.
In order to take into account environmental differences, quantify the speed of operation by normalizing to be as fair as possible in terms of Power-Performance-Area (PPA), such as the amount of computation, power, and circuit implementation area.
In cases where constant normalization is difficult, such as large environmental differences or difficulty in obtaining quantitative values, at the discretion of the contest judges, other information obtained from interviews with the participants will be used to reflect the results.

  • Completeness :Qualitative evaluation
  • Accuracy :Quantitative value
  • Operating speed : Quantitative value

Perspectives of Completion Evaluation

  • The quality of the report itself (clarity of each point, clarification of the areas of improvement, etc.)
  • Clarity, originality, and extensibility of the content which is thought out
  • Approach that has the potential to be used in general, not just in algorithm specific areas
  • Edge-implementation oriented by increasing processing efficiency
  • Unique features of edge implementation (power, implementation size, modularity, etc.)
  • Developmental considerations for remaining issues

Examples of Evaluation Points

  • Focus on AI models -> Novelty of model approach / Accuracy - model size balance / Model compression methods
  • Focus on RISC-V-> Power-Performance-Area comparison (Dhrystone-based, etc.) / HW control using only RISC-V without ARM core in FPGA except for boot / AI processing using RISC-V based low power architecture
  • Focus on system integration-> Optimize system level performance / Maximize FPGA resources / SW stack framework / Real-time integration with cloud

Submission Procedure for Inference Results

Instead of the usual prediction results file, you submit the source code for the trained model and the inference part. After submission, a prediction results file is automatically created and evaluated for size and inference speed, as well as recognition accuracy. Please refer to the readme of the distributed data for instructions on preparing the submission file.

* It takes time for evaluation results to be reflected on the leaderboard because it involves the execution of source code.
* Leaderboard ratings are not used for the final evaluation. Please use them as a reference.

Measurement of Algorithm Size and Inference Speed

The size and inference time of the submission file (a set of source code and trained models) are evaluated in the following procedure.

  1. Not eligible to the evaluation if the size of the submitted file exceeds the 3GB threshold.
  2. After extracting the submission files, the source code (and trained models) are run in the following environment to measure inference time and accuracy.
      - OS: Ubuntu 20.04
      - GPU: Nvidia A10G
      - CUDA: Version 11.3.1
      ※ Please see here for the Docker image of the execution environment and here for the Dockerfile.
  3. If the inference time exceeds the threshold of 5 [seconds/frame], it will be evaluated but not ranked (displayed as "-" on the leaderboard).
      ※ If the entire process, including loading the trained model, takes more than 3 hours, it will be considered an error and will not be evaluated.
  4. Only when the size of the submitted file and the inference time meet the threshold, the result will be shown on the leaderboard. (Inference time shown on the leaderboard is in [seconds/frame]).


Evaluation of Recognition Accuracy

  • Evaluated by the evaluation function mAP (mean average precision).
  • The evaluation value takes a value between 0 and 1. The higher the accuracy, the larger the value.


  • It is judged to be detected if the distance between the prediction area and the correct area is within 1.0[m].
  • The maximum number of predictions for each category per sample is 50.

Web Article Prize

  • This prize is open to those who write educational articles on the website, such as blogs, and publish links to their articles in the forum.
  • The organizer's office will check the contents of the submissions received by 23:59 on Sunday of  February 5, after the competition is over, to determine the prize winners.
  • Those who failed to submit final submissions are also eligible.

Premise of participation
・ Please understand the purpose set in the competition and build a system that is conscious of practicality. Practicality here means that it is fully automatic processing, high accuracy, high speed, low calculation amount (HW cost saving), scalable with respect to the amount of data, and high model interpretability.
・ Participation by cheating or ignoring the rules is not allowed.
・ It is prohibited to slander others or to act against public order and morals. If the secretariat determines that it is malicious, please be aware that there is a possibility of deprivation of winning qualifications and membership qualifications before participating.

Use of System
・ You may have one account per participant.
・ If you want to join as a team, you can create a team of up to five people by Dec 31, 2022. (Click here for how to create a team)

Handling of Information
・ Public disclosure of algorithms, ideas or other materials created to participate in this competition shall not be restricted, only if it is clearly stated that those are created to participate in this competition at the time of publication.
・ However, at the public disclosure, please specify it (including links) in the forum of this competition so that all participants can view it.

Use of Data
・ Use of the data other than provided data, and learned data shall not be restricted if the method allows verification of reproducibility for free. For example, the dataset with non-profit purpose, such as Waymo Open Dataset, can be used.
・ However, use of data provided by past AI Edge Contests is prohibited.
・ Modification of training data (including manual labeling and label rewriting) is allowed.
・ For API, the data that can be republished as an open source can be used.
・ Inference is performed on video-by-video basis. When tracking an object in videos, future information can be used if it is the data for test in the same video (tracking two-way). However use of the data in other videos is prohibited.

Creating algorithms
・ If you enter new data in the format provided in the competition, only the model for which the prediction result is automatically output will be evaluated.
・ The proposed method should be reproducible without any additional costs (you are not allowed to not use any paid external APIs, etc.), and the algorithms are meant to be used after this competition.

Way to implement
Use RISC-V Cores during object tracking tasks.
The cases where RISC-V is used in this contest are permitted and not permitted below.

【Permitted cases】
・ RISC-V is used as microcomputer controller during Deep Neural Network processing on FPGA.
・ Participant designed some special operator by extending RISC-V ISA to accelerate Deep Neural Network processing on FPGA
・ Use RISC-V core implemented on FPGA for a part of the processing in the measurement range.
・Using a board with a RISC-V-based SoC K210, cooperate with the DNN core in the SoC to implement object detection processing.

【NOT permitted cases】
・ Use RISC-V as result output only (not used in core processing or controller of component potion.)
・ Use a emulator of RISC-V (e.g. QEMU) on the top of ARM, and process the core part  in the emulator

The purpose of this contest is to develop human resources involved in the technology and application of the RISC-V, which is expected to be used in the Edge AI field in the future, and to educate the public on how to use RISC-V.

Judging criteria may be added in the future at the discretion of the Steering Committee or other relevant committee members at least one month before the contest deadline. If other cases arise, the review committee will deliberate on them and make a decision on an individual basis.

Host

 

Sponsors

               

                    

                 

     

Support

IEEE Japan Office
The Society of Instrument and Control Engineers (SICE)
The Japan Society for Precision Engineering (JSPE)
Japan Electronics and Information Technology Industries Association (JEITA)
The Institute of Electronics, Information and Communication Engineers (IEICE)
The Japanese Society for Artificial Intelligence

Steering Committee Members

  • Shinpei Kato Tokyo University
  • Naoki Suganuma Kanazawa University
  • Hiroaki Matsumoto Sony Semiconductor Solutions Corporation
  • Eisaku Ohbuchi Sony Semiconductor Solutions Corporation
  • Hironobu Fujiyoshi Chubu University
  • Masato Motomura Tokyo Institute of Technology
  • Hiroki Nakahara Tokyo Institute of Technology
  • Yoshiki Ninomiya Global Research Institute for Mobility in Society, Institutes of Innovation for Future Society, Nagoya University
  • Teruaki Sakata Hitachi, Ltd.
  • Kohei Ozaki Preferred Networks
  • Atsuto Suyama BOLDLY, Inc.
  • Masaki Hiraga Morpho, Inc.

How to get the KV206 board

1. Provided from this contest
- Although limited in number, the KV260 board will be provided after review for the contest participants. For those of you who wish to be provided, please apply through here.

2. Obtain from the website
- You can purchase from following.
https://www.mouser.jp/ProductDetail/Xilinx/SK-KV260-G?qs=DRkmTr78QATF92lTPoHh8Q%3D%3D
https://www.digikey.jp/ja/products/detail/amd-xilinx/SK-KV260-G-ED/13985275

Reference Environment (Software) * Scheduled to be released in early September
Learning PointPainting, inference environment and trained model are released. We are planning a phased release.

Step1.
We are building a reference environment using open data KITTI. Please use it to understand the method of PointPainting.
https://github.com/pometa0507/6th-ai-reference

Step2.
The reference environment (PointPainting learning, inference environment, and trained model) using the distributed data of this contest is open to the public.
https://github.com/pometa0507/6th-ai-reference2

Reference Environment (Hardware) * Scheduled to be released in late September
It will work with Xilinx FPGA boards, but operation is not guaranteed with other boards.

Online seminar to explain the reference implementation

Video will be released later.

Document:Software Hardware

Winners' solutions from previous contests

FPGA Implementation Tutorials for Beginners
Mr. Nakahara, a member of the Steering Committee, created a tutorial for beginners when applying for this contest.(Japanese only)

AI Edge Contest (Implementation Contest) Tutorial [1: Introduction]
AI Edge Contest (Implementation Contest) Tutorial [2: Learning on Google Golab]
Tutorial of AI Edge Contest (Mounting Contest) [3: Inference with Ultra96 board CPU]
AI Edge Contest (Implementation Contest) Tutorial [4: How to design an inference circuit in FPGA]

You will license your winning Submission and the source code used to generate the Submission under an Open Source Initiative-approved license (see www.opensource.org) that in no event limits commercial use of such code or model containing or depending on such code. As a reference, we will post a comparison table of representative open source writers.

License 
RequiredPermitted
Forbidden
Apache License 2.0 (Apache-2.0)Display copyright, Explicit change placementCommercial use, Modification, Distribution, Sub license, Patent grantUse trademark, Liability exemption
BSD License: See 3-clause BSD License and 2-clause BSD LicenseDisplay copyrightCommercial use, Modification, Distribution, Sub license
Use trademark, Liability exemption
GNU General Public License version 3 (GPL-3.0)Display copyright, Explicit change placement, Explicit sourceCommercial use, Modification, Distribution, Patent grant
Liability exemption,  Sub license
MIT License (MIT)Display copyrightCommercial use, Modification, Distribution, Sub license
Liability exemption

Disclosure policy

As a general rule, in accordance with Article 4, Paragraph 1 of the terms of participation, diclosing any contents such as insights and deliverables transmitted through the information or data provided by our company in relation to this competition is not permitted, however, only after the completion of this competition and for non-commercial purposes, it will be possible to disclose the contents within the score of the table below
Model *1
Public
Analysis results *2
Public
Public : Posting to social media sites, blogs and source repositories, and citing to papers
Restricted : Using in a limited range from research, education to seminars, where many unspecified people cannot access
*1 Execution unit source code and learned models
*2 The insights obtained using the information and data provided, or the solutions including scripts and processed data such as summary statistics

※Notes

・Although redistribution of the data itself is prohibited, you are allowed to publish some image data as the result of your analysis in your presentation materials at the award ceremony or in your own website articles, as long as you clearly state the source of the data.
・When disclosing information, please clearly state the credit: "Dataset used by Nagoya University, Tokai National Higher Education and Research System and Human Machine Harmonization System Consortium".
・It can be disclosed on this competition forum even during the term of this competition.
・When using the data in a paper, please use the following criteria as the scope of use of the data.
 - Extraction of general academic knowledge through statistical analysis
 - Use as teacher/evaluation data for machine learning (the resulting machine learning model must not be used commercially)
 - Excerpts of videos for illustration (only for academic publications, up to 10 images per article)

Q. There was an obvious mistake in the label of the training data. What should I do?
A. It is possible to correct the learning data according to the rules, so please delete or correct it. We check all kinds of data, but it is difficult to detect and correct 100% of mistakes, so we take the present result as "correct" and analyze it. Thank you for your understanding.


Q. I implemented it on an Ultra96 board. Please tell me how to make an SD card image for submission.
A. Please refer to the forum / article of the 2nd contest below for how to create an SD card image.

https://signate.jp/competitions/191/discussions/sd

▼ Special Contract on this Contest
In accordance with Article III “Prizes and Rights” of the special regulations established for this contest as described below, participants will either choose to make their own submission data, source code and other relevant items be licensed under an Open Source Initiative approved license (www.opensource.org) or not. This license imposes no restrictions on commercial use for licensed models, source code, and any results attained using said source code. Incidentally, the participants who will not choose this license will not be able to prize winner candidate, even though they can participate in the contest. In regard to posting and/or other publication on any social media site, blog or similar by the participant of information relating to any algorithm developed by said participant or any other materials produced for or related to this contest (including materials used for final submissions and/or final evaluations/inspections), no restrictions apply to posting and/or publication as long as the participant clearly explains that the posted/published items relate to this contest, and absolutely posts the positing and/or publication information (including the link URL to the pages) on the contest forum in order to let all the participants know it.


Terms of Participation in SIGNATE Competition

In order to participate in the Competition, you are required to agree to these Terms, in addition to the Terms of Use of SIGNATE.JP Site (hereinafter referred to as the “Terms of Use”). You should participate in the Competition after reading carefully and agreeing to these Terms. These Terms, the matters that are displayed as “additional matters” that you have agreed to when participating in a Competition, the Terms of Use and other terms and conditions that you have agreed to (hereinafter collectively referred to as “these Terms, etc.”) shall all be binding on the Participant.


Article 1 Definitions

1. For the purpose of these Terms, the following terms shall be defined as follows:

(1) “Site” means the website “SIGNATE (https://signate.jp)” on which the Competitions are posted.
(2) “Competition” means any competition on AI development or data analysis on the Site as held by the Host.
(3) “Host” is the host(s) of the Competition. The Host may be SIGNATE, Inc. (hereinafter referred to as the “Company”) or the Company’s client companies, affiliated companies, schools or organizations, etc. (hereinafter referred to as the “Client(s)”).
(4) “Participant(s)” means the member(s) (which mean “member(s)” defined in the Terms of Use, and the same shall apply hereinafter) who participate in a Competition.
(5) “Submissions” means, collectively, the analysis and prediction results, prediction models and reports, etc. as submitted in the Competition.
(6) “Final Submissions” means the Submissions submitted by a Participant that the Participant has specified as a final submission on the prescribed page in the Site by the time of completion of a Competition.
(7) “Winner Candidate” means the Participant who has received a notice from the Company that he/she is nominated as a winner candidate.
(8) “Submissions for Final Judgment” means the Submissions and other items designated by the Company as submitted by a Winner Candidate pursuant to the instructions of the Company.
(9) “Final Judgment” means the acceptance inspection and judgment, including reproducibility verification, by the Company for the Final Submissions and Submissions for Final Judgment of a Winner Candidate.
(10) “Winner” means the Winner Candidate who is informed by the Company that he/she has won a prize.
(11) “OSS” means software licensed based on OSS License Terms.
(12) “OSS License Terms” means any of the following license terms
(1) Either the GNU General Public License or the GNU Lesser General Public License published by the Free Software Foundation, Inc.;
(2) License terms listed at www.opensource.org/licenses/ or derivatives thereof;
(3) License terms that regard the software as “free software” or “open source software”; and
(4) License terms or agreements similar to the license terms listed in each of the three preceding items which request the user to disclose, distribute or license to a third party, or not to exercise, etc., the licensed software, its derivatives and the intellectual property rights associated therewith in whole or in part.

Article 2 Competition

1. A member who desires to participate in a Competition shall be required to agree to these Terms, etc. and to satisfy the conditions for participation as specified in each such Competition. Any person who is not a member shall not participate in any Competition.
2. Participants shall participate in each Competition in the manner as advised by the Company and shall be obligated to comply with the rules as prescribed in each Competition.
3. Participants may submit the Submissions for the assignment of a Competition during the period of such Competition and submit as many proposals on the method of solving the problem as specified by the Company to the Host by the end of the period of the said Competition.
4. Participants may submit Submissions in the form specified in the Competition and specify those Submissions as a Final Submission on the prescribed page in the Site by the end time specified by the said Competition.
5. Participants’ Final Submissions shall be evaluated in accordance with the evaluation method specified in the Competition and the final ranking shall be determined based on such evaluation.
6. Participants may, as a general rule, check their own evaluation results and the evaluation results of each of the other Participants for Submissions that may be evaluated quantitatively on the Site.
7. Participants shall be solely liable for their own Submissions, including the legality and non-infringement of the Submission.
8. Participants shall not submit any Submissions that have no direct relationship to each Competition.
9. Unless otherwise provided for, Participants may not directly communicate to, consult with, make a request to, solicit or take any other actions with the Host in respect of the matters related to a Competition during the period of the said Competition.
10. Participants shall direct any questions or concerns regarding any Competition to the Company or the third party designated by the Company in accordance with the procedures prescribed by the Company as posted on the Site.
11. Participants shall produce Submissions in compliance with the OSS License Terms related to the OSS when using or incorporating OSS in a Submission. However, Participants shall not use or incorporate OSS for which commercial use is prohibited in a Submission.
12. The Host shall not be obligated to pay any remuneration or other consideration for any act of the Participants in a Competition under any pretext. And the Company shall not be obligated to pay any remuneration or other consideration other than those prescribed in the following Article for any act of the Participants in a Competition.

Article 3 Reward and Vesting of Rights

1. Unless otherwise provided for, any Participant shall satisfy the requirements set forth in the following items in order to be entitled to receive a reward in any Competition that offers a reward:

(1) To be a winner;
(2) To agree to transfer to the Host and the relevant transferee of rights in such Competition all transferable rights, such as copyrights (including the rights as prescribed in Article 27 and Article 28 of the Copyright Act, and the same shall apply hereinafter), rights to obtain patents and know-how, etc. in and to all analysis and prediction results, prediction models, reports, etc., written explanations on algorithms, source code and reproduction method, etc. (although not limited to these), and the Submissions contained in the Final Submissions and Submissions for Final Judgment (hereinafter referred to as the “Rights”) along with a guarantee that the Participant has the authority to transfer such Rights;
(3) To guarantee that any relevant transferee of rights may use the Rights contained in the Final Submissions and Submissions for Final Judgment for its own business and other purpose without any restriction and to agree to their exclusive use of such Rights;
(4) To agree not to exercise moral rights to the Rights against the relevant transferee of rights;
(5) To enter into an agreement for the transfer of the Rights with the relevant eligible transferee of rights, including the guarantee of and agreement to the matters in the preceding three (3) items and other reasonable provisions;
(6) To have the personal identity of such Participant verified by the Company; and
(7) Not to breach any provision of these Terms, etc.

2. Any Winner Candidate shall, after having received a notice from the Company that he/she is nominated as a winner candidate, submit the Submissions for Final Judgment on or before the designated date and communicate the matters requiring confirmation or response in relation to the Final Submissions and the Submissions for Final Judgment to the Company on or before the designated date, in accordance with the instructions of the Company. The Company shall carry out the final judgment based on such matters requiring confirmation or response. If the Company receives no confirmation or response satisfactory to the Company on or before the designated date, the Company may exclude such Winner Candidate from the subject of the final judgment and the Winner Candidate shall not raise any objection thereto.
3. If the Company considers that the Final Submissions or Submissions for Final Judgment need to be amended or modified, or there occur any additional matters requiring confirmation, in the course of the final judgment, any Winner Candidate shall take action or make response in relation to the matters that require amendment or modification, or the matters requiring confirmation, on or before the designated date in accordance with the instructions of the Company. If the Company receives no action or response satisfactory to the Company on or before the designated date, the Company may exclude such Winner Candidate from the final judgment and the Winner Candidate shall not raise any objection thereto.
4. The Company shall determine the Winner through the final judgment and inform the Winner to that effect.

Article 4 Confidentiality

1. Any Participant shall treat any information and data that they receive from the Company in relation to Competitions as well as knowledge and products, etc. obtained using such information and data (including Participant Submissions; hereinafter referred to as the “Company-Provided Information”) as confidential information and shall not disclose the same to any third party and use the same for any purpose other than for such Competition and purpose specified by the Company separately; provided, however, that the confidential information shall not include any information that falls under any of the following items:

(1) Information that is known to the public at the time it was received;
(2) Information that is already possessed by the Participant at the time it was received (only in the case where such Participant may demonstrate such fact by reasonable means);
(3) Information that becomes known to the public without the fault of the Participant after it was received;
(4) Information that is independently developed by the Participant without reference to any information received; or
(5) Information that is rightfully received from any third party having a right to disclose such information without the obligations of confidentiality (only in the case where such Participant may demonstrate such fact by reasonable means).

2. Any Winner shall handle his/her Final Submissions and Submissions for Final Judgment in the same manner as Company-Provided Information after receiving notification that they are a winner. And Participant Submissions other than the Winner’s Final Submissions and Submissions for Final Judgment shall not be included as Company-Provided Information after the Company has determined the Winner notwithstanding the provisions of the preceding paragraph.
3. Any Participant may publish any algorithms that they have developed as well as any other materials they have created in connection with their participation in a Competition (including Final Submissions and Submissions for Final Judgment) after that Competition in accordance with the Competition Information Disclosure Policy (hereinafter, "Information Disclosure Policy") posted on the Site. However, Participants shall observe the following matters when publishing information and may not publish any materials prohibited by the Information Disclosure Policy:

(1) Clarify that the materials were created in connection with participation in the Competition;
(2) Give credit in accordance with the notation method prescribed in the Information Disclosure Policy when the materials to be published contain part of a dataset; and
(3) Clarify the location accessible to all Participants (including but not limited to the Competition forum and other locations designated by the Company) where the materials are published (including links, etc.) if publishing materials outside the Competition forum.

4. Any Participant shall delete or return to the Company the Company-Provided Information (excluding the information prescribed in paragraph 3) immediately after the completion of a Competition.
5. If there is any separate arrangement in relation to the confidential information in a Competition, the provisions of such arrangement shall prevail over the provisions of these Terms.
6. If any dispute occurs between a third party and the Host or the Company due to the breach by any Participant of the provisions of this Article and such other party makes any claim against the Company or the Host, such Participant shall compensate for any damage, loss, expenses (including, but not limited to, attorneys’ fees), lost profits and lost revenues, etc. incurred by the Company and the Host.
7. The provisions of this Article shall survive the termination of the relevant Competition or the Participant’s completion of the procedures for withdrawal from all services provided by the Company, with respect to the Company-Provided Information and the Winner’s Final Submissions and Submissions for Final Judgment for a period of five (5) years thereafter.

Article 5 Prohibited Acts of Participants

1. The Company shall prohibit Participants from engaging in any of the following acts in any Competition:

(1) An act of cracking, cheating, spoofing and other misconduct;
(2) An act of redistributing data files included in the dataset;
(3) An act of directly communicating to, consulting with, making a request to, soliciting or responding to solicitation or other activities to other Participants or the Host (other than the Company) without the involvement of the Company for the purpose of furthering the Participant’s own interests;
(4) Any profitmaking activities using the Competition (including but not limited to solicitation or scouting activities, and use for a third party in educational business, etc.) without the prior approval of the Company in writing or any other manner specified by the Company;
(5) An Act of transferring, offering as collateral or otherwise disposing of the Participants’ standing, or the rights or obligations, as a Participant in any Competition (except with the prior written consent of the Company);
(6) Acts that infringe upon the intellectual property rights, trade secrets or any other rights of third parties; and
(7) Any other act in breach of these Terms, etc.

2. If the Company deems that a Participant has engaged in, or may engage in, any of the prohibited acts as prescribed in the preceding paragraph, the Company may, without prior notice to the Participant, disqualify the Participant from the Competition in which the Participant participates, temporarily suspend the Participant from using some or all of the services provided by the Company, withdraw the Participant’s membership, claim damages from the Participant or take any other measures deemed necessary by the Company.

Article 6 Modification of Terms

1. The Company may modify, add or delete any provisions of these Terms from time to time without the approval of Participants.

August 17, 2022