Efficient Super-Resolution Challenge

Evaluation

The evaluation consists of the comparison of the x4 super-resolved images with the ground truth images and the reporting of the number of parameters (memory), FLOPs,  and inference time/runtime of the solution.

Only deep-learned solutions working with PyTorch are sought. Other solutions will be accepted but will not be officially ranked.

Note that we will rely on a self-reported number of parameters and runtime/inference time in the validation phase, while for the final test phase ranking the challenge organizers will check and run the provided solutions and compute the measures, such as runtime, parameters, and FLOPs.

The entry EFDN_baseline is the baseline created by the organizers based on the 1st place for the overall performance of the NTIRE2023 Efficient SR Challenge (The organizers have generated all reported baseline results using the NVIDIA RTX A6000 GPU. For consistency, it is recommended, though NOT mandatory, that you assess your model on the same GPU type).

For submitting the results, you need to follow these steps:

1. process the input images and keep the same name for the output image results as produced by your method (e.g., for an input file with the name "083.png" the output file should be "083.png") 
   Note that the output images should be saved with lossless compression and should have the pixel size of the input images x16.
2. create a ZIP archive containing all the output image results named as above and a readme.txt Note that the archive should not include folders, all the images/files should be in the root of the archive. To create the ZIP archive, select the 200 images and the readme.txt file under your root folder directly,  right-click your mouse, and select "Compression". 
3. the readme.txt file should contain the following lines filled in with the runtime per image (in seconds) of the solution, the number of model parameters, the GFLOPs, and 1 or 0 if employs extra data for training the models or not, an example of the baseline method EFDN is shown as below:
   Runtime per image [s] : 0.01669
Parameters : 276000
FLOPs [G]: 16.70
Extra Data [1] / No Extra Data [0] : 0
Other description : Model name: EFDN_baseline; GPU: NVIDIA RTX A6000
4. The last part of the file can have any description you want about the code producing the provided results (dependencies, links, scripts, etc.) The provided information is very important both during the validation period when different teams can compare their results/solutions and also for establishing the final ranking of the teams and their methods

The Final Evaluation Score

After the organizers receive all the submitted codes/checkpoints/results, four steps are adopted for the evaluation:

• Step 1: The organizers will execute each model five times to reevaluate all submitted methods on the same device, specifically the NVIDIA RTX 6000. The average results of these five runs will be documented for each metric.
• Step 2: To ensure PSNR consistency with the baseline method EFDN, PSNR checks will be conducted for all submitted methods. Any method with a PSNR below 26.90 dB on the DIV2K_LSDIR_valid dataset or less than 26.99 dB on the DIV2K_LSDIR_test datasets will be excluded from the comparison list for the remaining rankings.
• Step 3: For the rest, the Score_Runtime, Score_FLOPs, and the Score_Params will be calculated as follows:

Score_Runtime = exp(2*Runtime / Runtime_EFDN)

Score_FLOPs = exp(2*FLOPs / FLOPs_EFDN)

Score_Params = exp(2*Params / Params_EFDN)

• Step4: The final comparison score Score_Final will be calculated as follows:

Score_Final = 0.7*Score_Runtime + 0.15*Score_FLOPs + 0.15*Score_Params

Let's take the baseline as an example, given the results (i.e., average Runtime_EFDN = 16.69 ms, FLOPs_EFDN = 16.70 G, and Params_EFDN = 0.276 M) of EFDN, we have:

Score_Runtime = 7.3819

Score_FLOPs = 7.3819

Score_Params = 7.3819

Score_Final = 7.3819

❗ The ranking for each sub-track 💎 will be generated based on the corresponding Scores (i.e., Score_Runtime, Score_FLOPs, and Score_Params), while for the main track 🏆 , the ranking will be determined by the Score_Final. For all the scores,  the lower the better.

Efficient Super-Resolution Challenge

These are the official rules (terms and conditions) that govern how the NTIRE challenge on efficient super-resolution 2025 will operate. This challenge will be simply referred to as the "challenge" or the "contest" throughout the remaining part of these rules and may be named as the "NTIRE" benchmark, challenge, or contest, elsewhere (our webpage, our documentation, other publications).

In these rules, "we", "our", and "us" refer to the organizers (Yawei Li <yawei.li@vision.ee.ethz.ch>, Bin Ren <bin.ren@unitn.it>, Hang Guo <cshguo@gmail.com>, Zongwei Wu(zongwei.wu@uni-wuerzburg.de), and Radu Timofte <Radu.Timofte@uni-wuerzburg.de> from ETH Zurich, the University of Trento/Pisa, Tsinghua University, and the University of Wurzburg) of NTIRE challenge and "you" and "yourself" refer to an eligible contest participant.

Note that these official rules can change during the contest until the start of the final phase. If at any point during the contest, the registered participant considers that can not anymore meet the eligibility criteria or does not agree with the changes in the official terms and conditions then it is the responsibility of the participant to send an email to the organizers such that to be removed from all the records. Once the contest is over no change is possible in the status of the registered participants and their entries.

1. Contest description

This is a skill-based contest and chance plays no part in the determination of the winner (s).

The goal of the contest is to super-resolve an input image to an output image with a magnification factor x4 while the proposed solution is constrained on the following aspects: inference time, number of parameters, FLOPs, fidelity (PSNR), and the challenge is called efficient super-resolution.

The focus of the contest: it will be made available DIV2K and LSDIR datasets adapted for the specific needs of the challenge. The images in the two datasets have a large diversity of contents. Both datasets are divided into training, validation, and testing data. The challenge has one track. The aim is to devise a network that reduces one or several aspects such as runtime, parameters, and FLOPs of EFDN (https://arxiv.org/pdf/2204.08759) while at least maintaining a PSNR of 26.90dB on the DIV2K_LSDIR validation dataset, and a PSNR of 26.99 on the DIV2K_LSDIR test dataset. The participants will not have access to the ground truth images from the test data. The ranking of the participants is according to the performance of their methods on the test data. The participants will provide descriptions of their methods, details on (run)time complexity, the number of parameters, and (extra) data used for modeling. The winners will be determined according to their entries, the reproducibility of the results and uploaded codes or executables, and the above-mentioned criteria as judged by the organizers.

2. Tentative contest schedule

The registered participants will be notified by email if any changes are made to the schedule. The schedule is available on the NTIRE workshop web page and on the Overview of the Codalab competition.

3. Eligibility

You are eligible to register and compete in this contest only if you meet all the following requirements:

• you are an individual or a team of people willing to contribute to the open tasks, who accept to follow the rules of this contest
• you are not an NTIRE challenge organizer or an employee of NTIRE challenge organizers
• you are not involved in any part of the administration and execution of this contest
• you are not a first-degree relative, partner, or household member of an employee or of an organizer of the NTIRE challenge or of a person involved in any part of the administration and execution of this contest

This contest is void wherever it is prohibited by law.

Entries submitted but not qualified to enter the contest, it is considered voluntary and for any entry you submit NTIRE reserves the right to evaluate it for scientific purposes, however, under no circumstances will such entries qualify for sponsored prizes. If you are an employee, affiliated with or representant of any of the NTIRE challenge sponsors then you are allowed to enter the contest and get ranked, however, if you rank among the winners with eligible entries you will receive only a diploma award and none of the sponsored money, products or travel grants.

NOTE: industry and research labs are allowed to submit entries and to compete in both the validation phase and the final test phase. However, to get officially ranked on the final test leaderboard and to be eligible for awards the reproducibility of the results is a must, and, therefore, the participants need to make available and submit their codes or executables. All the top entries will be checked for reproducibility and marked accordingly.

We will have 3 categories of entries in the final test ranking:
1) checked with publicly released codes 
2) checked with publicly released executable
3) unchecked (with or without released codes or executables)

4. Entry

In order to be eligible for judging, an entry must meet all the following requirements:

Entry contents: the participants are required to submit image results and code or executables. To be eligible for prizes, the top-ranking participants should publicly release their code or executables under a license of their choice, taken among popular OSI-approved licenses (http://opensource.org/licenses) and make their code or executables online accessible for a period of not less than one year following the end of the challenge (applies only for top three ranked participants of the competition). To enter the final ranking the participants will need to fill out a survey (fact sheet) briefly describing their method. All the participants are also invited (not mandatory) to submit a paper for peer-reviewing and publication at the NTIRE Workshop and Challenges. To be eligible for prizes, the participants' scores must improve the baseline performance provided by the challenge organizers.

Use of data provided: all data provided by NTIRE are freely available to the participants from the website of the challenge under license terms provided with the data. The data are available only for open research and educational purposes, within the scope of the challenge. NTIRE and the organizers make no warranties regarding the database, including but not limited to warranties of non-infringement or fitness for a particular purpose. The copyright of the images remains in property of their respective owners. By downloading and making use of the data, you accept full responsibility for using the data. You shall defend and indemnify NTIRE and the organizers, including their employees, Trustees, officers, and agents, against any and all claims arising from your use of the data. You agree not to redistribute the data without this notice.

• Test data: The organizers will use the test data for the final evaluation and ranking of the entries. The ground truth test data will not be made available to the participants during the contest.
• Training and validation data: The organizers will make available to the participants a training dataset with ground truth images and a validation dataset without ground truth images. At the start of the final phase, the test data without ground truth images will be made available.
• Post-challenge analyses: the organizers may also perform additional post-challenge analyses using extra data, but without effect on the challenge ranking.
• Submission: the entries will be online and submitted via the CodaLab web platform. During the development phase, while the validation server is online, the participants will receive immediate feedback on validation data. The final evaluation will be computed automatically on the test data submissions, but the final scores will be released after the challenge is over.
• Original work, permissions: In addition, by submitting your entry into this contest you confirm that, to the best of your knowledge: - your entry is your own original work; and - your entry only includes material that you own, or that you have permission to use.

5. Potential use of entry

Other than what is set forth below, we are not claiming any ownership rights to your entry. However, by submitting your entry, you:

Are granting us an irrevocable, worldwide right and license, in exchange for your opportunity to participate in the contest and potential prize awards, for the duration of the protection of the copyrights to:

1. Use, review, assess, test, and otherwise analyze results submitted or produced by your code or executable and other material submitted by you in connection with this contest and any future research or contests by the organizers; and
2. Feature your entry and all its content in connection with the promotion of this contest in all media (now known or later developed);

Agree to sign any necessary documentation that may be required for us and our designees to make use of the rights you granted above;

Understand and acknowledge that us and other entrants may have developed or commissioned materials similar or identical to your submission and you waive any claims you may have resulting from any similarities to your entry;

Understand that we cannot control the incoming information you will disclose to our representatives or our co-sponsor’s representatives in the course of entering, or what our representatives will remember about your entry. You also understand that we will not restrict the work assignments of representatives or our co-sponsor’s representatives who have had access to your entry. By entering this contest, you agree that the use of information in our representatives’ or our co-sponsor’s representatives unaided memories in the development or deployment of our products or services does not create liability for us under this agreement or copyright or trade secret law;

Understand that you will not receive any compensation or credit for use of your entry, other than what is described in these official rules.

If you do not want to grant us these rights to your entry, please do not enter this contest.

6. Submission of entries

The participants will follow the instructions on the CodaLab website to submit entries

The participants will be registered as mutually exclusive teams. Each team is allowed to submit only one single final entry. We are not responsible for entries that we do not receive for any reason, or for entries that we receive but do not work properly.

The participants must follow the instructions and the rules. We will automatically disqualify incomplete or invalid entries.

7. Judging the entries

The board of NTIRE will select a panel of judges to judge the entries; all judges will be forbidden to enter the contest and will be experts in causality, statistics, machine learning, computer vision, or a related field, or experts in challenge organization. A list of the judges will be made available upon request. The judges will review all eligible entries received and select three winners for each competition track based on the prediction score on test data. The judges will verify that the winners complied with the rules, including that they documented their method by filling out a fact sheet.

The decisions of these judges are final and binding. The distribution of prizes according to the decisions made by the judges will be made within three (3) months after the completion of the last round of the contest. If we do not receive a sufficient number of entries meeting the entry requirements, we may, at our discretion based on the above criteria, not award any or all of the contest prizes below. In the event of a tie between any eligible entries, the tie will be broken by giving preference to the earliest submission, using the time stamp of the submission platform.

8. Prizes and Awards

The financial sponsors of this contest are listed on NTIRE 2025 workshop web page. There will be economic incentive prizes and travel grants for the winners (based on availability) to boost contest participation; these prizes will not require participants to enter into an IP agreement with any of the sponsors, to disclose algorithms, or deliver source code to them. The participants affiliated with the industry sponsors agree to not receive any sponsored money, product or travel grant in the case they will be among the winners.

Incentive Prizes for each track competition (tentative, the prizes depend on attracted funds from the sponsors)

• 1st place: ?00$ + ?GPU + award certificate
• 2nd place: ?00$ + ?GPU + award certificate
• 3rd place: ?00$ + award certificate

9. Other Sponsored Events

Publishing papers is optional and will not be a condition to entering the challenge or winning prizes. The top-ranking participants are invited to submit a paper following CVPR2025 author rules, for peer-reviewing to the NTIRE workshop.

The results of the challenge will be published together with NTIRE 2025 workshop papers in the 2025 CVPR Workshops proceedings.

The top-ranked participants and participants contributing interesting and novel methods to the challenge will be invited to be co-authors of the challenge report paper which will be published in the 2025 CVPR Workshops proceedings. A detailed description of the ranked solution as well as the reproducibility of the results are a must to be an eligible co-author.

10. Notifications

If there is any change to data, schedule, instructions of participation, or these rules, the registered participants will be notified at the email they provided with the registration.

Within seven days following the determination of winners, we will send a notification to the potential winners. If the notification that we send is returned as undeliverable, or you are otherwise unreachable for any reason, we may award the prize to an alternate winner, unless forbidden by applicable law.

The prize such as money, product, or travel grant will be delivered to the registered team leader given that the team is not affiliated with any of the sponsors. It's up to the team to share the prize. If this person becomes unavailable for any reason, the prize will be delivered to the authorized account holder of the e-mail address used to make the winning entry.

If you are a potential winner, we may require you to sign a declaration of eligibility, use, indemnity, liability/publicity release, and applicable tax forms. If you are a potential winner and are a minor in your place of residence, we require that your parent or legal guardian be designated as the winner, and we may require that they sign a declaration of eligibility, use, indemnity, and liability/publicity release on your behalf. If you, (or your parent/legal guardian if applicable), do not sign and return these required forms within the period listed on the winner notification message, we may disqualify you (or the designated parent/legal guardian) and select an alternate selected winner.

The terms and conditions are inspired by and use verbatim text from the `Terms and conditions' of ChaLearn Looking at People Challenges, of the AIM 2019, 2020, 2021, 2022, 2023 and 2024 challenges and of the NTIRE 2017, 2018, 2019, 2020, 2021, 2022, 2023 and 2024 challenges.

Organizers

The NTIRE challenge on Efficient Super-Resolution is organized jointly with the NTIRE 2025 workshop. The results of the challenge will be published at the NTIRE 2025 workshop and in the CVPR 2025 Workshops proceedings.

Yawei Li (yawei.li [at] vision.ee.ethz.ch), Bin Ren (bin.ren [at] unitn.it), Hang Guo (cshguo [at] gmail.com), Zongwei Wu (zongwei.wu [at] uni-wuerzburg.de)and Radu Timofte (Radu.Timofte [at] uni-wuerzburg.de) are the contact persons and direct managers of the NTIRE challenge.

More information about the NTIRE workshop and challenge organizers is available here: https://cvlai.net/ntire/2025/