Academic Journal
Q1Foundations and Trends in Computer Graphics and Vision
About Foundations and Trends in Computer Graphics and Vision
Foundations and Trends in Computer Graphics and Vision is a scholarly journal published by Now Publishers Inc. SCImago 2025 lists it in Q1, with an SJR of 3.472 and H-index of 32.
Coverage: 2005-2007, 2009-2016, 2018-2025. Research categories: Computer Vision and Pattern Recognition (Q1).
Source-backed journal facts
Topics in published research
Advanced Vision and Imaging; Image Retrieval and Classification Techniques; Advanced Image and Video Retrieval Techniques; Computer Graphics and Visualization Techniques; Advanced Neural Network Applications; Medical Image Segmentation Techniques.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
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2024-12-18 · DOI: 10.1561/0600000112Beyond Fairness in Computer Vision: A Holistic Approach to Mitigating Harms and Fostering Community-Rooted Computer Vision Research
Timnit Gebru, Remi Denton
2024-09-30 · DOI: 10.1561/0600000102Multimodal Foundation Models: From Specialists to General-Purpose Assistants
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Stanley H. Chan, Nicholas Chimitt
2023-10-30 · DOI: 10.1561/0600000103Towards Better User Studies in Computer Graphics and Vision
Zoya Bylinskii, Aaron Hertzmann, Yile Zhang, Laura Herman et al.
2023-05-08 · DOI: 10.1561/0600000106An Introduction to Neural Data Compression
Yibo Yang, Stephan Mandt, Lucas Theis
2023-04-25 · DOI: 10.1561/0600000107Learning-based Visual Compression
Ruolei Ji, Lina J. Karam
2023-01-09 · DOI: 10.1561/0600000101Vision-Language Pre-Training: Basics, Recent Advances, and Future Trends
Zhe Gan, Linjie Li, Chunyuan Li, Lijuan Wang et al.
2022-12-05 · DOI: 10.1561/0600000105Semantic Image Segmentation: Two Decades of Research
Gabriela Csurka, Riccardo Volpi, Boris Chidlovskii
2022-10-19 · DOI: 10.1561/0600000095Video Summarization Overview
Mayu Otani, Yale Song, Yang Wang
2022-10-12 · DOI: 10.1561/0600000099A Comprehensive Review of Modern Object Segmentation Approaches
Yuanbo Wang, Unaiza Ahsan, Hanyan Li, Matthew Hagen et al.
2022-10-05 · DOI: 10.1561/0600000097Deep Learning for Image/Video Restoration and Super-resolution
A. Murat Tekalp
2022-05-05 · DOI: 10.1561/0600000100Deep Learning for Multimedia Forensics
Irene Amerini, Aris Anagnostopoulos, Luca Maiano, Lorenzo Ricciardi Celsi et al.
2021-08-31 · DOI: 10.1561/0600000096Computer Vision for Autonomous Vehicles
Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger et al.
2020-07-06 · DOI: 10.1561/0600000079Discrete Graphical Models — An Optimization Perspective
Bogdan Savchynskyy
2019-12-10 · DOI: 10.1561/0600000084Line Drawings from 3D Models
Pierre Bénard, Aaron Hertzmann
2019-09-11 · DOI: 10.1561/0600000075Reviews
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Version History
October 4, 2026 at 8:43 pm
September 13, 2026