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:40.60
Contributing Best Scientists:820
H5-index:
Papers published by Best Scientists1500
Research Ranking (Computer Science)3
Conference Call for Papers
ICCV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
Papers in the main technical program must describe high-quality, original research. Topics of interest include all aspects of computer vision and pattern recognition including, but not limited to
3D Computer Vision
Action Recognition
Big data and Large Scale Methods
Biometrics, face and gesture
Biomedical image analysis
Computational photography, photometry, shape from X
Deep Learning
Low-level vision and Image Processing
Motion and Tracking
Optimization methods
Recognition: detection, categorization, indexing and matching
Robot Vision
Segmentation, grouping and shape representation
Statistical learning
Video: events, activities and surveillance
Vision for X
Overview
Top Research Topics at International Conference on Computer Vision?
Artificial intelligence (94.84%)
Computer vision (43.04%)
Pattern recognition (29.60%)
The main research concerns discussed in International Conference on Computer Vision are Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Machine learning.
It focuses on Artificial intelligence research which is adjacent to topics in Algorithm.
The study on Computer vision presented is investigated in conjunction with research in Robustness (computer science).
The concepts on Pattern recognition presented in the event can also apply to other research fields, including Contextual image classification, Facial recognition system and Feature (computer vision).
Facial recognition system studies tackled cover an aspect of the field of Face (geometry).
The conference facilitates discussions on Feature extraction that incorporate concepts from other fields like Artificial neural network and Visualization.
The conference facilitated presentations on Image segmentation research, particularly Scale-space segmentation and Segmentation-based object categorization.
What are the most cited papers published at the conference?
Object recognition from local scale-invariant features (12389 citations)
Fast R-CNN (9748 citations)
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (9051 citations)
Research areas of the most cited articles at International Conference on Computer Vision:
The conference publications primarily focus on research topics in Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Object detection.
The Artificial intelligence research tackled in the conference papers is interrelated with Machine learning which concerns subjects like Training set.
While the conference papers focused on Pattern recognition, they were also able to explore topics like 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
Statistics
The previous edition focused in particular on these issues:
The objective of International Conference on Computer Vision is to combine knowledge in the areas of Artificial intelligence, Computer vision, Pattern recognition, Image (mathematics) and Machine learning.
The studies on Artificial intelligence discussed can also contribute to research in the domains of Algorithm and Code (cryptography).
The event dives deep in exploring the relationship between the study of Algorithm and Point cloud.
The event aims to address concerns in Computer vision, specifically in the areas of Object detection, Motion (physics), Pixel, Monocular and Pose.
Domain (software engineering), Set (abstract data type) and Feature (computer vision) are some topics wherein Pattern recognition research discussed in it have an impact.
It holds forums on Machine learning that merges themes from other disciplines such as Task (project management) and Benchmark (computing).
The most cited articles from the last conference are:
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction Without Convolutions (15 citations)
Swin Transformer: Hierarchical Vision Transformer Using Shifted Windows (13 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
Top authors and change over time
The top authors publishing at International Conference on Computer Vision (based on the number of publications) are:
Luc Van Gool (80 papers) published 24 papers at the last edition, 23 more than at the previous edition,
Andrew Zisserman (59 papers) published 7 papers at the last edition,
Cordelia Schmid (49 papers) published 9 papers at the last edition,
Larry S. Davis (46 papers) published 6 papers at the last edition,
Jitendra Malik (46 papers) published 3 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
Top affiliations and change over time
Only papers with recognized affiliations are considered
The top affiliations publishing at International Conference on Computer Vision (based on the number of publications) are:
Microsoft (310 papers) published 60 papers at the last edition, 58 more than at the previous edition,
Carnegie Mellon University (278 papers) published 47 papers at the last edition, 43 more than at the previous edition,
Chinese Academy of Sciences (271 papers) published 99 papers at the last edition, 89 more than at the previous edition,
Massachusetts Institute of Technology (222 papers) published 37 papers at the last edition, 33 more than at the previous edition,
The Chinese University of Hong Kong (205 papers) published 62 papers at the last 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, 5.29% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 30.39% were posted by at least one author from the top 10 institutions publishing at the conference. Another 11.75% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.78% of all publications and 37.08% 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.
