Image and Vision Computing

149.2k citations
4.1k papers · · active since 1950

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Video Surveillance and Tracking Methods
    • Face and Expression Recognition
    • Image Retrieval and Classification Techniques
    • Face recognition and analysis
    • Medical Image Segmentation Techniques

Papers in

    • Advanced Vision and Imaging 818
    • Advanced Image and Video Retrieval Techniques 741
    • Medical Image Segmentation Techniques 531
    • Video Surveillance and Tracking Methods 526
    • Image Retrieval and Classification Techniques 511
    • Face recognition and analysis 375
    • Human Pose and Action Recognition 366

Image and Vision Computing

3.9k papers receiving 137.6k citations

Peers

Image and Vision Computing
Comparison fields: 5 of 236
  • Computer Vision and Pattern Recognition 106.8k
  • Media Technology 18.3k
  • Human-Computer Interaction 7.2k
  • Signal Processing 12.3k
  • Computer Graphics and Computer-Aided Design 3.6k
Replace Computer Vision and Image Understanding with:
Computer Vision and Image Understanding United States
IEEE Transactions on Multimedia China
Multimedia Tools and Applications China
Pattern Recognition Letters China
IEEE Transactions on Intelligent Transportation Systems China
Journal of the Optical Society of America A United States
IEEE Sensors Journal China
IEEE Transactions on Instrumentation and Measurement China
Neurocomputing China
ACM Computing Surveys United States
Image and Vision Computing relative to Computer Vision and Image Understanding United States Computer Vision and Image Understanding's profile →
Citations per field
00.5×1.5×
Computer Vision and Image Understanding · 1×
Citations per year

Countries where authors publish in Image and Vision Computing

Since Specialization
Citations

This map shows the geographic impact of research published in Image and Vision Computing. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Image and Vision Computing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Image and Vision Computing more than expected).

Fields of papers published in Image and Vision Computing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Image and Vision Computing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Image and Vision Computing.

About Image and Vision Computing

The 4.1k papers published in Image and Vision Computing in the last decades have received a total of 149.2k indexed citations . Papers published in Image and Vision Computing usually cover Computer Vision and Pattern Recognition (3.5k papers), Media Technology (492 papers), Computer Graphics and Computer-Aided Design (147 papers), Signal Processing (319 papers) and Human-Computer Interaction (157 papers) specifically the topics of Advanced Vision and Imaging (818 papers), Advanced Image and Video Retrieval Techniques (741 papers), Medical Image Segmentation Techniques (531 papers), Video Surveillance and Tracking Methods (526 papers), Image Retrieval and Classification Techniques (511 papers), Robotics and Sensor-Based Localization (476 papers), Face recognition and analysis (375 papers) and Human Pose and Action Recognition (366 papers). The most active scholars publishing in Image and Vision Computing are Jan Flusser, Ronald Poppe, Gérard Medioni, Yang Chen, Jiřı́ Matas, Maja Pantić, Shaogang Gong, Ondřej Chum, Zhengyou Zhang and Chris Taylor.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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