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IEEE

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Location: Waikoloa , United States

Submission deadline: 7/6/2022

Conference dates: 1/3/2023 - 1/7/2023

Research H-index
75

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 18 797 1315 74

Call for Papers

Application areas include, but are not limited to:
Agriculture
Animals / Insects
Arts / games / social media
Biomedical / healthcare / medicine
Commercial / retail
Education
Embedded sensing / real-time techniques
Environmental monitoring / climate change / ecology
Food science and nutrition
Psychology and cognitive science
Remote Sensing
Robotics
Smartphones / end-user devices
Social good
Structural engineering / civil engineering
Virtual / augmented reality
Visualization
Authors are also encouraged to submit more traditional computer vision algorithms papers. Topics of interest include, but are not limited to:
3D computer vision
Adversarial learning, adversarial attack and defense methods
Biometrics, face, gesture, body pose
Computational photography, image and video synthesis
Explainable, fair, accountable, privacy-preserving, ethical computer vision
Image recognition and understanding (object detection, categorization, segmentation, scene modeling, visual reasoning)
Low-level and physics-based vision
Machine learning architectures, formulations, and algorithms (including transfer, low-shot, semi-, self-, and un-supervised learning)
Video recognition and understanding (tracking, action recognition, etc.)
Vision + language and/or other modalities

Overview

This comprehensive ranking presents a curated list of scientific conferences in the field of Engineering and Technology, meticulously prepared by Research.com. As one of the leading websites for science research across all major fields, Research.com has been providing trusted data on scientific contributions since 2014. The ranking reflects a rigorous evaluation process, underscoring our commitment to credibility and excellence in academic assessment.

Conferences are ranked based on a unique bibliometric score developed by Research.com. This score is computed through a robust methodology that factors in the estimated h-index as well as the number of leading scientists who have participated in each conference throughout the preceding three years. The Impact Score values underlying the rankings were collected on 2024-11-27, ensuring relevance and accuracy with the latest available data.

The ranking process involved a thorough examination of more than 2,262 conferences. These conferences were carefully selected following a detailed inspection and rigorous analysis of over 26,934 scientific documents, all published within the last three years. Contributions from 9,385 leading and highly respected scientists in Engineering and Technology were scrutinized to ensure a comprehensive and objective evaluation.

For further insight into the methodology applied in computing these ranking scores, please refer to our Methodology Page.

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.

The top authors publishing at Workshop on Applications of Computer Vision (based on the number of publications) are:

  • Luc Van Gool (18 papers) published 2 papers at the last edition the same number as at the previous edition,
  • Larry S. Davis (16 papers) published 2 papers at the last edition the same number as at the previous edition,
  • Gerard Medioni (14 papers) absent at the last edition,
  • Min C. Shin (13 papers) absent at the last edition,
  • Ram Nevatia (12 papers) absent at the last 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.

Only papers with recognized affiliations are considered

The top affiliations publishing at Workshop on Applications of Computer Vision (based on the number of publications) are:

  • University of Southern California (44 papers) published 4 papers at the last edition, 1 less than at the previous edition,
  • Carnegie Mellon University (39 papers) published 9 papers at the last edition, 4 more than at the previous edition,
  • University of Maryland, College Park (32 papers) published 3 papers at the last edition, 1 less than at the previous edition,
  • Australian National University (26 papers) published 11 papers at the last edition, 9 more than at the previous edition,
  • ETH Zurich (25 papers) published 6 papers at the last edition, 4 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.

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.

During the most recent 2020 edition, 4.24% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 15.79% were posted by at least one author from the top 10 institutions publishing at the conference. Another 8.86% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.28% of all publications and 57.06% 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.

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.

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).

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

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