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ECCV 2026 Reviewer Guidelines

 

Thank you for reviewing for  ECCV 2026! To maintain a high-quality technical program, we rely very much on the time and expertise of our reviewers. This document explains what is expected of all members of the Reviewing Committee for ECCV 2026. For further details, please consult the ECCV 2026 Reviewer Tutorial Slides.
 

Reviewing Timeline

  • Tuesday, March 31, 2026: Reviewers receive assigned papers; review period starts
  • Tuesday, April 21, 2026: Deadline for submitting reviews 
  • Tuesday, May 12, 2026: Reviewers receive author rebuttals; discussion period starts
  • Tuesday, May 12 to Wednesday, May 20, 2026: Discussion phase
  • Wednesday, May 20, 2026: Deadline for submitting final reviewer recommendations

The reviewing deadlines will be STRICT. Reviewers who submit timely and high-quality reviews will be considered for Outstanding Reviewer awards and recommended for future conferences. 

Please note that these reviewing guidelines contain changes with respect to past conferences. In particular, ECCV 2026 introduces the possibility for authors to specify the Contribution Type of their paper. Below you will find more information about these changes and how to incorporate them in the reviews.

Reviewing In a Nutshell

Each paper that is accepted should be technically sound and make a contribution to the field. Look for what is good or stimulating in the paper, and what knowledge advancement it has made. We recommend that you embrace novel, brave concepts, even if they have not been tested on many datasets. For example, the fact that a proposed method does not exceed the state-of-the-art accuracy on an existing benchmark dataset is not grounds for rejection by itself. Rather, it is important to weigh both the novelty and potential impact of the work alongside the reported performance. Minor flaws that can be easily corrected should not be a reason to reject a paper. Above all, you should be specific and detailed in your reviews. Your discussion, more than your score, will help the authors, fellow reviewers, and Area Chairs understand the basis for your recommendation. You should include specific feedback on ways the authors can improve their papers. Be sure to avoid committing common reviewer errors, e.g. novelty fallacy; consult the ECCV 2026 Reviewer Tutorial Slides for more details and examples.

Check your papers

As soon as you get your reviewing assignment, please go through all the papers to make sure that (a) you have no obvious conflict of interest (see “Avoid Conflicts of Interest” below) and (b) you feel comfortable reviewing the paper assigned. If issues with either of these points arise, please contact the Area Chair right away as instructed in the detailed emails you will receive during the process.

Know the policies

Please read the ECCV 2026 Submission Policies carefully to familiarize yourself with all official policies the authors are expected to follow. If you come to believe that a paper may be in violation of any of these policies, please contact the Area and Program Chairs. In the meantime, proceed to review the paper assuming no violation has taken place and describe the potential policy violation in the confidential comments field. Please also carefully read the LLM policy for reviewers in the “Ethics for Reviewing Papers” below and  Reviewer FAQs.

NEW! Contribution Types for Papers and for Reviewers

In ECCV 2026, authors assign one Contribution Type to their paper (see Guidance to Authors on Contribution Types for more information on how authors make this choice). The goal of the Contribution Types and accompanying guidelines is to support fair, nuanced, and context-aware reviewing at ECCV. This attribute specifies how you should assess a paper. For example, a Datasets/Benchmarks paper should not be penalized if it does not propose a novel method. For detailed instructions on reviewing with Contribution Types, see Guidance to Reviewers on Contribution Types. 

Moreover, during registration, reviewers may select one or more Contribution Types of papers that they would prefer to review (with Algorithms/General as the default option). These preferences are not binding and do not guarantee that you will only be assigned papers of those types, but they will increase the likelihood that you will be reviewing a paper that better matches your style.
 

Responsible Reviewing Policy

At ECCV 2026, reviewers are expected to provide fair and thoughtful reviews that demonstrate meaningful engagement with the submission. Highly irresponsible reviewing includes: unreasonably short reviews that fail to reference specific technical content from the paper; reviews containing only generic comments that could apply to any submission without addressing the paper's actual contribution; reviews with demonstrable factual errors about the paper's methodology or results that indicate superficial reading; and reviews generated by or assisted by Large Language Models. This policy does not penalize reviewers for holding different technical opinions, missing minor details, writing concise but substantive reviews, or having legitimate disagreements with other reviewers or Area Chairs. If a review is flagged as highly irresponsible, it will undergo an oversight process managed by the Program Chairs (PCs). Any reviewer whose review is deemed to be "highly irresponsible" will face a desk rejection of all papers on which they are an author at the discretion of the PCs.

Reviewing Deadline Policy

At ECCV 2026, reviewers are also expected to provide timely reviews. Historically, previous ECCV conferences (and ICCV, CVPR, and NeurIPS, amongst others) faced challenges with some reviewers failing to meet the review submission deadlines. It came to be accepted that there was an unofficial grace period after the reviewing deadline. In some cases, reviewers failed to respond to multiple reminders and did not submit their reviews at all. This necessitated Area Chairs (ACs) to follow up diligently with late reviewers, as well as assign emergency reviewers to ensure each paper received a minimum of three reviews. Over the years, this has added to the already large workload and stress of the conference organizers. To improve the review process and uphold the conference’s high standards, ECCV 2026 will strictly enforce the reviewing deadline. Any reviewer who fails to submit their assigned reviews by the deadline will face a desk rejection of all papers on which they are an author at the discretion of the PCs. This policy aims to ensure fairness and accountability across the reviewing process while reducing the burden on ACs and other conference organizers.

There will be multiple emails sent out to all reviewers as a reminder to submit reviews in a timely manner. Additionally, the co-authors of reviewers who have not submitted their reviews will also be notified that their submission may be desk rejected if all authors do not submit their reviews in time.

 

Ethics for Reviewing Papers

1. Respect anonymity in the review process

Our Submission Policies have instructed authors to make reasonable efforts to hide their identities, including omitting their names, affiliations, and acknowledgments. This information will of course be included in the final published version of the manuscript. Reviewers should not take active steps to discover the identity of the authors, and make all efforts to keep their own identity invisible to the authors.

With the increase in popularity of arXiv preprints, sometimes the authors of a paper may already be known to the reviewer. Posting to arXiv is NOT considered a violation of anonymity on the part of the authors, and in most cases, reviewers who happen to know (or suspect) the authors’ identity can still review the paper as long as they feel that they can do an impartial job. An important general principle is to make every effort to treat papers fairly whether or not you know (or suspect) who wrote them. If you do not know the identity of the authors at the start of the process, DO NOT attempt to find out the authorship of a submission.

2. Protect ideas

As a reviewer for ECCV, you have the responsibility to protect the confidentiality of the ideas represented in the papers you review. ECCV submissions are not published documents. The work is considered new or proprietary by the authors; otherwise, they would not have submitted it. Of course, their intent is to ultimately publish to the world, but most of the submitted papers will not appear in the ECCV proceedings. Thus, it is likely that the paper you have in your hands will be refined further and submitted to some other journal or conference. Sometimes the work is still considered confidential by the authors' employer(s). These organizations do not consider sending a paper to ECCV for review to constitute a public disclosure. Protection of the ideas in the papers you receive means:

  • You should not show the paper to anyone else, including colleagues or students, unless you have asked them to write a review or to help with your review.
  • You should not show any results, videos/images, code, or any of the supplementary material to non-reviewers.
  • You should not use ideas/code from papers you review to develop your own ideas/code.
  • After the review process, you should destroy all copies of papers and supplementary material and erase any code that the authors submitted as part of the supplementary, and any implementations you have written to evaluate the ideas in the papers, as well as any results of those implementations.

3. Avoid conflicts of interest

As a reviewer of an ECCV paper, it is important for you to avoid any conflict of interest. There should be absolutely no question about the impartiality of any review. Thus, if you are assigned a paper where your review would create a possible conflict of interest, you should return the paper as early as possible and not submit a review. Conflicts of interest include (but are not limited to) situations in which:

  • You work at the same institution as one of the authors.
  • You have been directly involved in the work and will be receiving credit in some way. If you are a member of an author's thesis committee, and the paper is about their thesis work, then you were involved.
  • You suspect that others might perceive a conflict of interest in your involvement.
  • You have collaborated with one of the authors in the past three years (more or less). Collaboration is usually defined as having written a paper or grant proposal together, although you should use your judgment.
  • You were the MSc/PhD advisor or advisee of one of the authors. Most funding agencies and publications typically consider advisees to represent a lifetime conflict of interest. ECCV, similarly to other computer vision conferences, has traditionally been more flexible than this, but you should think carefully before reviewing a paper you know to be written by a former advisor or advisee, especially a recent one.

While the organizers make every effort to avoid such conflicts in the review assignments, they may nonetheless occasionally arise. If you recognize the work or the author and feel it could present a conflict of interest, contact your Area Chair as soon as possible so they can find someone else to review it.

4. Large Language Model (LLM) Ethics

ECCV2026 does not allow the use of Large Language Models or online chatbots such as ChatGPT in any part of the reviewing process. There are two main reasons: (a) Reviewers must provide comments that faithfully represent their original opinions on the papers being reviewed. It is unethical to resort to Large Language Models (e.g., an offline system) to automatically generate reviewing comments that do not originate from the reviewer's own opinions; (b) Online chatbots such as ChatGPT collect conversation history to improve their models. Therefore, their use in any part of the reviewing process would violate the ECCV confidentiality policy. Any violation of this policy will be considered “highly irresponsible” behavior on the part of a reviewer and will result, at the discretion of the Program Chairs, in the desk rejection of all papers on which the reviewer is an author. 

5. Be professional

Belittling or sarcastic comments have no place in the reviewing process. The most valuable comments in a review are those that help the authors understand the shortcomings of their work and how they might improve it. Write a courteous, informative, incisive, and helpful review that you would be proud to sign with your name (were it not anonymous).
 

How to Write Good Reviews

Please see also our ECCV 2026 Reviewer Tutorial Slides.

 

Check your papers

As soon as you get your reviewing assignment, please go through all the papers to make sure that (a) you have no obvious conflict of interest (see “Avoid Conflicts of Interest” above) and (b) you feel comfortable reviewing the paper assigned. If issues with either of these points arise, please contact the Area Chair right away as instructed in the detailed emails you will receive during the process.

Know the policies

Please read the Submission Policy carefully to familiarize yourself with all official policies the authors are expected to follow. If you come to believe that a paper may be in violation of any of these policies, please contact the Area Chair handling the paper. In the meantime, proceed to review the paper, assuming no violation has taken place.

Be Mindful of Contribution Types

Each paper that is accepted should be technically sound and make a contribution to the field. Look for what is good or stimulating in the paper, and what knowledge advance it has made. Minor flaws that can be easily corrected should not be a reason to reject a paper. Since computer vision research encompasses a wide range of work—from theoretical foundations to practical systems, from new algorithms to community datasets, and from early-stage ideas to mature deployments, a single set of uniform review criteria is therefore neither appropriate nor desirable. Thus in ECCV 2026, we have introduced Contribution Types to support fair, nuanced, and context-aware reviewing. Please refer to the Guidance to Reviewers on Contribution Types document for details.

Be Detailed

Take the time to write good reviews. Ideally, you should read a paper and then think about it over the course of several days before you write your review.

While length does not make a review good, short reviews tend to be enigmatic and so unhelpful to authors, other reviewers, and Area Chairs. If you have agreed to review a paper, you should take enough time to write a thoughtful and detailed review.

Your main critique of the paper should be written in terms of a list of strengths and weaknesses. You can use bullet points here, but also explain your arguments. Bullet lists with one short phrase per bullet are NOT a detailed review. Your detailed review, more than your score, will help the authors, fellow reviewers, and Area Chairs understand the basis for your recommendation, so please be thorough.

Be Specific

Be specific about novelty. Claims in a review that the submitted work “has been done before” MUST be backed up with specific references and an explanation of how closely they are related. The same MUST be done also for a positive review. Be sure to summarize what novel aspects are most interesting in the Strengths section.

Be specific when you suggest that the writing needs to be improved. If there is a particular section that is unclear, point it out and give suggestions for how it can be clarified.

In the discussion of related work and references, simply saying "this is well known" or "this has been common practice in the industry for years" is not sufficient: cite specific publications, including books or public disclosures of techniques.

Do not reject papers solely because they are missing citations or comparisons to prior work that has only been published without review (e.g., arXiv or technical reports). Refer to the FAQ below for more details on handling arXiv prior art.

Give Feedback to Improve Submissions

Please include specific feedback on ways the authors can improve their papers. Be generous about giving the authors new ideas for how they can improve their work. You might suggest a new technical tool that could help, a dataset that could be tried, an application area that might benefit from their work, or a way to generalize their idea to increase its impact.

If you think the paper is out of scope for ECCV's subject areas, clearly explain why in the review. Then suggest other publication possibilities (journals, conferences, workshops) that would be a better match for the paper. However, unless the area mismatch is extreme, you should keep an open mind, because we want a diverse set of good papers at the conference.

Be Mindful of Your Tone

The tone of your review is important. A harshly written review will be resented by the authors, regardless of whether your criticisms are true. If you take care, it is always possible to word your review constructively while staying true to your thoughts about the paper.

Avoid referring to the authors in the second person (“you”). It is best to avoid the term “the authors” as well, because you are reviewing their work and not the person. Instead, use the third person (“the paper”). Referring to the authors as “you” can be perceived as being confrontational, even though you may not mean it this way.

Finally, keep in mind that a thoughtful review not only benefits the authors, but also yourself. Your reviews are read by other reviewers and especially the Area Chairs, in addition to the authors. Unlike the authors, the Area Chairs know your identity. Being a helpful reviewer will generate good will towards you in the research community – and may even help you to win an Outstanding Reviewer award.
 

What Reviewers Should Look Out for in Papers

In addition to correctly assessing the Contribution Types (see Guidance to Reviewers on Contribution Types), reviewers should also familiarize themselves with the Suggested Practices for Authors and, more specifically, look for the following aspects:

 

Check for Reproducibility

To improve reproducibility in AI research, we highly encourage authors to voluntarily submit their code as part of supplementary material, especially if they plan to release it upon acceptance. Reviewers may optionally check this code to ensure the paper's results are reproducible and trustworthy, but are not required to. All code/data should be reviewed confidentially and kept private, and deleted after the review process is complete. We expect (but do not require) that the accompanying code will be submitted with accepted papers.

Check for Data Contribution

Datasets  and/or benchmarks are a significant part of Computer Vision research. If a paper is claiming a dataset and/or benchmark as one of its main scientific contributions by selecting Datasets/Benchmarks Contribution Type, it is mandatory that the dataset and/or benchmark a will be made publicly available no later than the camera-ready deadline. For further details, please refer to the  Guidance to Authors on Contribution Types.

Check for Attribution of Data Assets

Authors are advised that they need to cite data assets used (e.g., datasets or code) much like papers. As a reviewer, please carefully check if a paper has adequately cited data assets used in the paper. 

Check for Use of Personal Data and Human Subjects

If a paper is using personal data or data from human subjects, the authors must have an ethics clearance from an institutional review board (IRB, or equivalent) or clearly describe that ethical principles have been followed. If there is no description of how ethical principles were ensured or GLARING violations of ethics (regardless of whether discussed or not), please inform the Area Chairs and the Program Chairs, who will follow on each specific case. Reviewers shall avoid dealing with such issues by themselves directly. For more information, see also the Ethics Guidelines.

In this regard, if a paper uses an existing public dataset that is released by other researchers/research organizations, we encourage, but do not require them to include a discussion of IRB related issues in the paper. Reviewers, hence, should not penalize a paper if such a discussion is NOT included.

Check for Discussion of Negative Societal Impact

The ECCV community has not put as much emphasis on the awareness of possible negative societal impact as other AI communities so far, but this is an important issue. We aim to raise awareness without introducing a formal policy (yet). As a result, authors are encouraged to include a discussion on potential negative societal impact. Reviewers should weigh the inclusion of a meaningful discussion POSITIVELY. Reviewers should NOT reject a paper solely based on that the paper has not included such a discussion, as we do not have a formal policy requiring that. The Ethics Guidelines provide a non-exhaustive list of potential negative societal impact.

Check for Discussion of Limitations

Discussing limitations used to be commonplace in our community, but seems to be increasingly lost. We point out the importance of discussing limitations, especially to new authors. Therefore, authors are encouraged to explicitly and honestly discuss limitations. Reviewers should weigh the inclusion of an honest discussion POSITIVELY, instead of penalizing the papers for including it. We note that a paper is not required to have a separate section to discuss limitations, so it cannot be the sole factor for rejection.

Check for Ethical Concerns

As computer vision research and applications have increasing real-world impact, the likelihood of meaningful social benefit increases, but so does the attendant risk of harm. The research community should consider not only the potential benefits but also the potential negative societal impacts of computer vision research, and adopt measures that enable positive trajectories to unfold while mitigating risk of harm. During the ECCV review process, reviewers will have the ability to flag papers with significant ethical concerns. These will be referred to an ethics committee, which will assess the situation and advise the program chairs. The program chairs reserve the right to reject papers with grave ethical issues, but expect this to occur only in exceptional circumstances. Please see the Ethics Guidelines for details. Note that accepted papers need to adhere to the Springer Nature Code of Conduct for Book Authors.