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:33.20
Contributing Best Scientists:622
H5-index:
Papers published by Best Scientists869
Research Ranking (Computer Science)4
Conference Call for Papers
Papers in the main technical program must describe high-quality, original research. Topics of interest include the following aspects of computer vision and pattern recognition (in alphabetical order):
3D from a single image and shape-from-x
3D shape modeling and processing
Action and behavior recognition
Adversarial learning
Biometrics
Body gestures and pose
Computational photography
Datasets and evaluation
Detection and localization in 2D and/or 3D
Efficient training and inference methods
Explainable AI for CV
Faces
Fairness, accountability, transparency, and ethics in vision
First person (Egocentric) vision
Image and video manipulation detection
Image and video retrieval
Image and video synthesis
Low-level and physics-based vision
Low-shot learning
Machine learning architectures and formulations
Medical, biological, and cell microscopy
Motion and tracking
Neural generative models
Optimization and learning methods
Recognition and classification
Representation learning
Scene analysis and understanding
Scene text and document understanding
Segmentation, grouping, and shape
Semi / Weak / Self / Unsupervised Learning
Stereo, 3D from multiview and other sensors
Transfer learning
Video analysis and understanding
Vision + language
Vision + other modalities
Vision applications and systems
Vision for and autonomous vehicles
Vision for robotics and embodied vision
Visual reasoning and logical representation
Overview
Top Research Topics at European Conference on Computer Vision?
Artificial intelligence (77.41%)
Computer vision (40.60%)
Pattern recognition (27.58%)
The conference aims to foster the development of research in Artificial intelligence, Computer vision, Pattern recognition, Image (mathematics) and Machine learning.
The event facilitated presentations on Artificial intelligence research, particularly Segmentation, Object (computer science), Deep learning, Feature (computer vision) and Convolutional neural network.
The conference concentrated on Segmentation research, specifically Image segmentation and Scale-space segmentation.
Pixel, Tracking (particle physics), Pose, Object detection and Optical flow are all aspects of Computer vision discussed in the event.
Topics in Pattern recognition explored in the conference were investigated in conjunction with research in Facial recognition system, Face (geometry), Representation (mathematics) and Benchmark (computing).
What are the most cited papers published at the conference?
Microsoft COCO: Common Objects in Context (14384 citations)
SSD: Single Shot MultiBox Detector (11100 citations)
SURF: speeded up robust features (10783 citations)
Research areas of the most cited articles at European Conference on Computer Vision:
The conference publications primarily tackle Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Image (mathematics).
Issues in Pattern recognition were discussed in the conference articles, taking into consideration concepts from other disciplines like Feature (computer vision), Representation (mathematics), Facial recognition system, Face (geometry) and Pascal (programming language).
The conference articles explore issues in Machine learning which can be linked to other research areas like Cognitive neuroscience of visual object recognition and Training set.
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:
Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Image (mathematics) are among the topics commonly tackled in European Conference on Computer Vision.
The studies tackled, which mainly focus on Artificial intelligence, apply to Code (cryptography) as well.
The research on Pattern recognition discussed in the event draws on the closely related field of Pixel.
The overlapping concepts between Artificial neural network and Algorithm are the key highlights of Computer vision study.
Machine learning research featured in European Conference on Computer Vision incorporates concerns from various other topics such as Adversarial system, Representation (mathematics), Robustness (computer science) and Benchmark (computing).
Object (computer science) works presented in it have a specific focus on Object detection.
The most cited articles from the last conference are:
End-to-End Object Detection with Transformers (474 citations)
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (330 citations)
DeepIM: Deep Iterative Matching for 6D Pose Estimation (231 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 European Conference on Computer Vision (based on the number of publications) are:
Luc Van Gool (87 papers) published 22 papers at the last edition, 8 more than at the previous edition,
Andrew Zisserman (62 papers) published 7 papers at the last edition the same number as at the previous edition,
Ming-Hsuan Yang (50 papers) published 11 papers at the last edition, 4 less than at the previous edition,
Marc Pollefeys (42 papers) published 7 papers at the last edition, 1 more than at the previous edition,
Philip H. S. Torr (40 papers) published 9 papers at the last edition, 4 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 European Conference on Computer Vision (based on the number of publications) are:
Microsoft (254 papers) published 44 papers at the last edition, 17 more than at the previous edition,
Chinese Academy of Sciences (189 papers) published 90 papers at the last edition, 53 more than at the previous edition,
French Institute for Research in Computer Science and Automation (186 papers) published 8 papers at the last edition the same number as at the previous edition,
Carnegie Mellon University (179 papers) published 44 papers at the last edition, 13 more than at the previous edition,
ETH Zurich (168 papers) published 53 papers at the last edition, 23 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 2020 edition, 3.49% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 26.60% were posted by at least one author from the top 10 institutions publishing at the conference. Another 12.20% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.88% of all publications and 41.32% 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.
