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 Scientists3340
Research Ranking (Computer Science)1
Research Ranking (Electronics and Electrical Engineering)32
Research Ranking (Electronics and Electrical Engineering)14
Research Ranking (Neuroscience)10
Research Ranking (Computer Science)1
Conference Call for Papers
Topics of interest include all aspects of computer vision and pattern recognition including, but not limited to:
3D from multi-view and sensors
3D from single images
Adversarial attack and defense
Autonomous driving
Biometrics
Computational imaging
Computer vision for social good
Computer vision theory
Datasets and evaluation
Deep learning architectures and techniques
Document analysis and understanding
Efficient and scalable vision
Embodied vision: Active agents, simulation
Explainable computer vision
Humans: Face, body, pose, gesture, movement
Image and video synthesis and generation
Low-level vision
Machine learning (other than deep learning)
Medical and biological vision, cell microscopy
Multimodal learning
Optimization methods (other than deep learning)
Photogrammetry and remote sensing
Physics-based vision and shape-from-X
Recognition: Categorization, detection, retrieval
Representation learning
Robotics
Scene analysis and understanding
Segmentation, grouping and shape analysis
Self-& semi-& meta-& unsupervised learning
Transfer/ low-shot/ continual/ long-tail/ learning
Transparency, fairness, accountability, privacy, and ethics in vision
Video: Action and event understanding
Video: Low-level analysis, motion, and tracking
Vision + graphics
Vision, language, and reasoning
Vision applications
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:
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 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
Top affiliations and change over time
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.
