Ranking & Metrics Conference Call for Papers Other Conferences in United States
CVPR 2022 : IEEE/CVF Conference on Computer Vision and Pattern Recognition

CVPR 2022 : IEEE/CVF Conference on Computer Vision and Pattern Recognition

New Orleans , United States

Submission Deadline: Tuesday 16 Nov 2021

Conference Dates: Jun 21, 2022 - Jun 21, 2022

Research
Impact Score 63.10

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 63.10
Contributing Best Scientists: 1132
H5-index:
Papers published by Best Scientists 3340
Research Ranking (Computer Science) 1
Research Ranking (Electronics and Electrical Engineering) 32

Conference Call for Papers

Review Process: By submitting a paper to CVPR, the authors agree to the review process and understand that papers are processed by the Toronto Paper Matching System (TPMS) to match each manuscript to the best possible area chairs and reviewers.

Confidentiality: The review process of CVPR is confidential. Reviewers are volunteers; they are not part of the CVPR organization and their efforts are greatly appreciated. The practice of keeping all information confidential during the review is part of the standard communication to all reviewers. Misuse of confidential information is a severe professional failure and appropriate measures will be taken when brought to the attention of the CVPR organizers. It should be noted, however, that the organization of CVPR is not and cannot be held responsible for the consequences when reviewers break confidentiality.

Conflict Responsibilities: It is the primary author\'s responsibility to ensure that all authors on their paper have registered their institutional conflicts into the submission system – CMT3 (see details under Domain Conflicts below). If a paper is found to have an undeclared or incorrect institutional conflict, the paper may be summarily rejected. To avoid undeclared conflicts, the author list is considered to be final after the submission deadline and no changes are allowed for accepted papers.

Double blind review: CVPR reviewing is double blind, in that authors do not know the names of the area chair/reviewers of their papers, and the area chairs/reviewers cannot, beyond reasonable doubt, infer the names of the authors from the submission and the additional material. Do not provide information that may identify the authors in the acknowledgments (e.g., co-workers and grant IDs) and in the supplemental material (e.g., titles in the movies, or attached papers). Also do not provide links to websites that identify the authors. Violation of any of these guidelines may lead to rejection without review. If you need to cite a different paper of yours that is being submitted concurrently to CVPR or another venue, the authors should (1) cite these papers; (2) argue in the body of your paper why your CVPR paper is non-trivially different from these concurrent submissions; and (3) include anonymized versions of those papers in the supplemental material.

Plagiarism: Plagiarism consists of appropriating the words or results of another, without credit. CVPR 2022\'s policy on plagiarism is to refer suspected cases to the IEEE Intellectual Property office, which has an established mechanism for dealing with plagiarism and wide powers of excluding offending authors from future conferences and from IEEE journals. You can find information on this office, their procedures, and their definitions of five levels of plagiarism at this webpage. We will be actively checking for plagiarism. Furthermore, the paper matching system is quite accurate. As a result, it regularly happens that a paper containing plagiarized material goes to a reviewer from whom material was plagiarized; experience shows that such reviewers pursue plagiarism cases enthusiastically.

Dual/Double Submissions: The goals of CVPR are to publish exciting new work for the first time and to avoid duplicating the effort of reviewers. By submitting a manuscript to CVPR, the authors acknowledge that it has not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journal, conference or workshop, or archival forum. Furthermore, no publication substantially similar in content has been or will be submitted to this or another conference, workshop, or journal during the review period. Violation of any of these conditions will lead to rejection, and will be reported to the other venue to which the submission was sent.

A publication, for the purposes of this policy, is defined to be a written work longer than four pages (excluding references) that was submitted for review by peers for either acceptance or rejection, and, after review, was accepted. In particular, this definition of publication does not depend upon whether such an accepted written work appears in a formal proceedings or whether the organizers declare that such work “counts as a publication”.

As per PAMI TC motion, the above definition does not consider an arXiv.org pre-print as a publication because it cannot be rejected. It also excludes university technical reports, which are typically not peer reviewed. However, this definition of publication does include peer-reviewed workshop papers, even if they do not appear in a proceedings, if their length is more than four pages (excluding citations). Given this definition, any submission to CVPR should not have substantial overlap with prior publications or other concurrent submissions.

A submission with substantial overlap is one that shares 20 percent or more material with previous or concurrently submitted publications. Authors are encouraged to contact the Program Chairs about clarifications on borderline cases.

Note that a technical report (departmental, arXiv.org, etc.) version of the submission that is put up without any form of direct peer-review is NOT considered prior art and should NOT be cited in the submission.

Attendance responsibilities: The authors agree that if the paper is accepted, at least one of the authors will register for the conference and present the paper there.

Publication: All accepted papers will be made publicly available by the Computer Vision Foundation (CVF) two weeks before the conference. Authors wishing to submit a patent understand that the paper\'s official public disclosure is two weeks before the conference or whenever the authors make it publicly available, whichever is first. The conference considers papers confidential until published two weeks before the conference, but notes that multiple organizations will have access during the review and production processes, so those seeking patents should discuss filing dates with their IP council. The conference assumes no liability for early disclosures. More information about CVF is available at http://www.cv-foundation.org/.

Publicity, social media: Papers submitted to CVPR must not be discussed with the press until they have been officially accepted for publication. Work explicitly identified as a CVPR submission also may not be advertised on social media. Please see the FAQ section for more details. Violations may result in the paper being summarily rejected or removed from the conference and proceedings.

Authors acting as reviewers: Given the growth of the number of paper submissions, we expect all authors to be willing to serve as reviewers as well. With a large enough pool of reviewers, we expect that reviewers will be sent on the order of five papers to review. Our timeline expects that papers will go to reviewers about December 16, 2021, and reviews should be returned on or before January 14, 2022.

Overview

Top Research Topics at Computer Vision and Pattern Recognition?

  • Artificial intelligence (94.95%)
  • Computer vision (42.90%)
  • Pattern recognition (32.71%)

The conference focuses on Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Machine learning. The study on Artificial intelligence presented in Computer Vision and Pattern Recognition intersects with subjects under the field of Algorithm. Many of the studies tackled connect Computer vision with a similar field of study like Robustness (computer science).

The concepts on Pattern recognition presented in Computer Vision and Pattern Recognition can also apply to other research fields, including Contextual image classification, Facial recognition system and Feature (computer vision). The featured Facial recognition system research is covered under the field of Face (geometry). The studies tackled, which mainly focus on Feature extraction, apply to Visualization as well.

The conference centers on topics in Machine learning, with a focus on Deep learning. The presentations discussing Image segmentation offer insights in topics such as Scale-space segmentation and Segmentation-based object categorization. Most of the Convolutional neural network studies addressed also intersect with Artificial neural network.

What are the most cited papers published at the conference?

  • Deep Residual Learning for Image Recognition (74743 citations)
  • ImageNet: A large-scale hierarchical image database (26601 citations)
  • Histograms of oriented gradients for human detection (24038 citations)

Research areas of the most cited articles at Computer Vision and Pattern Recognition:

The conference articles mainly deal with areas of study such as Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Machine learning. The Artificial intelligence research presented in the published papers places emphasis on topics like Image segmentation, Object detection, Segmentation, Contextual image classification and Convolutional neural network. The most cited papers address concerns in Pattern recognition which are intertwined with other disciplines, such as Artificial neural network, Facial recognition system, Cognitive neuroscience of visual object recognition and Feature (computer vision).

What topics the last edition of the conference is best known for?

  • Artificial intelligence
  • Computer vision
  • Machine learning

The previous edition focused in particular on these issues:

The foci of the conference are Artificial intelligence, Computer vision, Pattern recognition, Image (mathematics) and Machine learning. It links adjacent topics like Artificial intelligence with Code (cryptography). In the event, Frame (networking) and Representation (mathematics) are investigated in conjunction with one another to address concerns in Computer vision research.

The concepts on Pattern recognition presented in Computer Vision and Pattern Recognition can also apply to other research fields, including Domain (software engineering), Feature (computer vision) and Benchmark (computing). Machine learning research featured in the conference incorporates concerns from various other topics such as Generalization and Task (project management). Artificial neural network and Algorithm are closely related fields of research discussed in the event.

The most cited articles from the last conference are:

  • Pre-Trained Image Processing Transformer (97 citations)
  • NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections (73 citations)
  • Exploring Simple Siamese Representation Learning (64 citations)

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Research.com

The top authors publishing at Computer Vision and Pattern Recognition (based on the number of publications) are:

  • Luc Van Gool (130 papers) published 16 papers at the last edition, 6 more than at the previous edition,
  • Thomas S. Huang (107 papers) published 1 paper at the last edition, 4 less than at the previous edition,
  • Ming-Hsuan Yang (101 papers) published 4 papers at the last edition, 5 less than at the previous edition,
  • Marc Pollefeys (98 papers) published 9 papers at the last edition, 2 more than at the previous edition,
  • Larry S. Davis (95 papers) published 8 papers at the last edition, 2 more than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at Computer Vision and Pattern Recognition (based on the number of publications) are:

  • Microsoft (756 papers) published 60 papers at the last edition, 6 less than at the previous edition,
  • Carnegie Mellon University (671 papers) published 49 papers at the last edition, 2 less than at the previous edition,
  • Chinese Academy of Sciences (534 papers) published 128 papers at the last edition, 34 more than at the previous edition,
  • Massachusetts Institute of Technology (466 papers) published 36 papers at the last edition, 3 more than at the previous edition,
  • Tsinghua University (445 papers) published 112 papers at the last edition, 41 more than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Research.com

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

Research.com

During the most recent 2021 edition, 3.28% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 27.47% were posted by at least one author from the top 10 institutions publishing at the conference. Another 12.14% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.38% of all publications and 39.02% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Research.com

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

Research.com

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Research.com

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Research.com

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Previous Editions

CVPR 2022 : IEEE/CVF Conference on Computer Vision and Pattern Recognition

Jun 21, 2022 - Jun 21, 2022

New Orleans , United States, United States

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