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:9.50
Contributing Best Scientists:332
H5-index:
Papers published by Best Scientists411
Research Ranking (Computer Science)36
Research Ranking (Electronics and Electrical Engineering)564
Research Ranking (Electronics and Electrical Engineering)390
Research Ranking (Computer Science)33
Conference Call for Papers
The British Machine Vision Conference (BMVC) is one of the major international conferences on computer vision and related areas. It is organised by the British Machine Vision Association (BMVA). The 33rd BMVC will now be a hybrid event from 21st—24th November 2022. Our local in-person meeting will be held at The Kia Oval (Home of Surrey County Cricket Club, https://events.kiaoval.com/).
Authors are invited to submit full-length high-quality papers in image processing, computer vision, machine learning and related areas for BMVC 2022. Submitted papers will be refereed on their originality, presentation, empirical results, and quality of evaluation. Accepted papers will be included in the conference proceedings published and DOI-indexed by BMVA. Past proceedings can be found online: here.
Please note that BMVC is a single-track meeting with oral and poster presentations. The abstract submission deadline is Friday 22nd July 2022 and the paper submission deadline is Friday 29th July 2022 (both 23:59, GMT). Submission instructions are available on the BMVC 2022 website. Submitted papers should not exceed 9 pages (references are excluded, but appendices are included).
Topics include, but are not limited to:
2D object recognition
3D computer vision
3D object recognition
Action and behavior recognition
Adversarial learning, adversarial attack and defense methods
Biometrics, face, gesture, body pose
Computational photography
Datasets and evaluation
Efficient training and inference methods for networks
Explainable AI, fairness, accountability, privacy, transparency and ethics in vision
Image and video retrieval
Image and video synthesis
Image classification
Low-level and physics-based vision
Machine learning architectures and formulations
Medical, biological and cell microscopy
Motion and tracking
Optimization and learning methods
Pose estimation
Representation learning
Scene analysis and understanding
Transfer, low-shot, semi- and un- supervised learning
Video analysis and understanding
Vision + language, vision + other modalities
Vision applications and systems, vision for robotics and autonomous vehicles
“Brave new ideas”
Overview
Top Research Topics at British Machine Vision Conference?
Artificial intelligence (76.95%)
Computer vision (45.81%)
Pattern recognition (30.08%)
The scientific interests tackled in British Machine Vision Conference are Artificial intelligence, Computer vision, Pattern recognition, Image (mathematics) and Algorithm.
The in-depth study on Artificial intelligence also explores topics in the intersecting field of Machine learning.
British Machine Vision Conference explores issues in Computer vision which can be linked to other research areas like Set (abstract data type) and Robustness (computer science).
The research on Pattern recognition featured in British Machine Vision Conference combines topics in other fields like Cognitive neuroscience of visual object recognition and Representation (mathematics).
It concentrated on Segmentation research, specifically Scale-space segmentation and Image segmentation.
Scale-space segmentation research presented is mostly focused on the subject of Segmentation-based object categorization.
What are the most cited papers published at the conference?
Deep face recognition (3620 citations)
Return of the Devil in the Details: Delving Deep into Convolutional Nets (2144 citations)
A Spatio-Temporal Descriptor Based on 3D-Gradients (1545 citations)
Research areas of the most cited articles at British Machine Vision Conference:
The conference publications mostly deal with topics like Artificial intelligence, Computer vision, Pattern recognition, Image (mathematics) and Object (computer science).
The studies tackled in the published papers, which mainly focus on Artificial intelligence, apply to Machine learning as well.
The most cited articles explore topics in Computer vision which can be helpful for research in disciplines like Set (abstract data type) and Robustness (computer science).
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 British Machine Vision Conference (based on the number of publications) are:
Andrew Zisserman (30 papers) published 4 papers at the last edition, 3 more than at the previous edition,
Horst Bischof (28 papers) published 2 papers at the last edition, 1 more than at the previous edition,
Luc Van Gool (25 papers) absent at the last edition,
Shaogang Gong (22 papers) published 1 paper at the last edition, 1 less than at the previous edition,
Tao Xiang (20 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.
Research.com
Top affiliations and change over time
Only papers with recognized affiliations are considered
The top affiliations publishing at British Machine Vision Conference (based on the number of publications) are:
University of Oxford (56 papers) published 7 papers at the last edition, 1 more than at the previous edition,
Queen Mary University of London (45 papers) published 4 papers at the last edition, 2 less than at the previous edition,
ETH Zurich (38 papers) published 7 papers at the last edition, 4 more than at the previous edition,
Microsoft (30 papers) published 2 papers at the last edition, 2 less than at the previous edition,
Chinese Academy of Sciences (29 papers) published 6 papers at the last edition, 5 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 2017 edition, 11.65% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 21.43% were posted by at least one author from the top 10 institutions publishing at the conference. Another 10.44% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.88% of all publications and 47.25% 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).
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
