Academic Journal
Q1International Journal of Computer Vision
About International Journal of Computer Vision
International Journal of Computer Vision is a scholarly journal published by Springer Netherlands. SCImago 2025 places it in Q1 with an SJR of 3.103 and an H-index of 242.
Its listed coverage is 1987-2026 and its research categories include Artificial Intelligence (Q1); Computer Vision and Pattern Recognition (Q1); Software (Q1). The 2025 dataset reports 405 documents and 8679 citations across the latest three-year reporting window.
About the International Journal of Computer Vision (IJCV)
The International Journal of Computer Vision (IJCV) is a leading peer-reviewed academic journal dedicated to the advancement of computer vision research. Since its inception in 1987, IJCV has been a vital platform for researchers, scientists, and practitioners to publish groundbreaking work in the field of computer vision, image processing, and machine learning. Published by Springer, the journal continues to set high standards for innovation, rigor, and academic excellence.
Focus and Scope
The International Journal of Computer Vision covers a wide range of topics within the field of computer vision. This includes, but is not limited to:
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Image segmentation and object recognition
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Motion analysis and tracking
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3D reconstruction and shape modeling
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Deep learning for vision tasks
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Visual perception and scene understanding
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Face and gesture recognition
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Computational photography and augmented reality
IJCV welcomes both theoretical and application-driven research, providing a comprehensive overview of advancements that bridge the gap between academic theory and real-world implementation. The journal encourages interdisciplinary contributions that combine computer vision with robotics, artificial intelligence (AI), neuroscience, and more.
High Impact and Academic Prestige
Recognized globally for its high impact factor and scholarly influence, the International Journal of Computer Vision consistently ranks among the top journals in the field. Its rigorous peer-review process ensures the publication of high-quality articles that push the boundaries of what is possible with visual data analysis.
IJCV is widely cited by researchers and referenced in major academic conferences such as CVPR, ICCV, ECCV, and NeurIPS. The journal is indexed in leading databases including Scopus, Web of Science, and Google Scholar, making it easily discoverable by academics and professionals worldwide.
Why Publish in IJCV?
Publishing in the International Journal of Computer Vision offers numerous benefits:
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Global Reach: With a vast readership across academia and industry, your research gains international visibility.
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Reputation: IJCV’s strong reputation enhances the credibility and impact of your work.
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Rigorous Review Process: Each submission undergoes a detailed peer-review by top experts in the field.
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Open Access Options: Authors can choose open-access publication for broader dissemination.
For Researchers and Readers
Whether you're a researcher seeking the latest trends in computer vision or a professional looking for innovative solutions, IJCV is an essential resource. The journal publishes regular issues throughout the year, featuring original articles, review papers, and special issues on emerging topics.
Journal Metrics
Metrics can change by reporting year. Verify time-sensitive values with the publisher or indexing service.
Aims & Scope
Scope of the International Journal of Computer Vision (IJCV)
The International Journal of Computer Vision (IJCV) is a prestigious, peer-reviewed academic journal that serves as a leading platform for publishing cutting-edge research in the field of computer vision. Established as one of the most respected journals in the domain, IJCV plays a critical role in shaping the direction of research and development in computer vision, image analysis, machine learning, and artificial intelligence.
Core Focus Areas
The scope of the International Journal of Computer Vision covers a broad range of topics within the field. It includes foundational theories, algorithmic advancements, and practical applications of computer vision technologies. Major areas of focus include:
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Image and Video Processing
Research related to filtering, enhancement, restoration, and compression of images and video. -
Object Recognition and Detection
Techniques for detecting, classifying, and recognizing objects in still images and video streams. -
3D Reconstruction and Scene Understanding
Studies on 3D modeling from 2D images, depth estimation, and understanding complex visual environments. -
Motion and Tracking
Algorithms for tracking moving objects, optical flow analysis, and motion interpretation. -
Deep Learning in Computer Vision
Application of neural networks, particularly convolutional neural networks (CNNs) and transformers, to vision tasks. -
Medical Image Analysis
Innovations in analyzing medical images for diagnostics, treatment planning, and monitoring. -
Facial Recognition and Biometrics
Biometric identification systems, facial feature analysis, and security-focused computer vision applications.
Interdisciplinary Impact
IJCV not only promotes innovation in core vision technologies but also encourages interdisciplinary research where computer vision intersects with areas such as:
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Robotics and autonomous systems
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Augmented and virtual reality (AR/VR)
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Natural language processing (NLP) and multimodal AI
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Computational photography
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Human-computer interaction (HCI)
The journal's aim is to bridge theoretical advances with real-world applications, thereby making a significant impact on industries like healthcare, automotive, surveillance, entertainment, and e-commerce.
Publication Standards
The International Journal of Computer Vision maintains rigorous peer-review standards and publishes high-quality, original research papers, comprehensive surveys, and insightful technical notes. Authors are expected to contribute novel findings with strong theoretical foundations and validated empirical results.
Global Reach and Academic Recognition
IJCV is indexed in major databases like Scopus, Web of Science, and Google Scholar, and enjoys a high impact factor, making it a sought-after venue for top-tier research publications. It attracts contributions from renowned researchers and practitioners worldwide, reflecting its global relevance and scholarly influence.
Recent Research Articles
Latest publications matched automatically by ISSN.
Learning Generalizable Semantic Radiance Fields with Cross-Reprojection Attention
Yueqi Duan, Fangfu Liu, Jiawei Chi, Hanyang Wang et al.
2026-09 · DOI: 10.1007/s11263-026-03020-wMotionStruct4D: Discovering Motion Structure of Gaussian Splatting for Video-to-4D Generation
Jia-Xing Zhong, Kai Lu, Jiaojiao Ye, Niki Trigoni et al.
2026-09 · DOI: 10.1007/s11263-026-02992-zDual Adaptive Visual-Semantic Prompt Collaboration for Generalized Zero-Shot Learning
Huajie Jiang, Zhengxian Li, Yuankai Qi, Yongli Hu et al.
2026-09 · DOI: 10.1007/s11263-026-02998-7Two-Stage Multi-Modal Fusion with Adaptive Alignment for Action Quality Assessment
Kanglei Zhou, Ruizhi Cai, Xinning Wang, Yijian Zheng et al.
2026-09 · DOI: 10.1007/s11263-026-02960-7OpenVid++: A Large-scale High-quality Dataset for Text-to-video Generation
Kepan Nan, Tiehan Fan, Rui Xie, Penghao Zhou et al.
2026-09 · DOI: 10.1007/s11263-026-02989-8MonoSOWA++: Universal Autolabeling Pipeline for Monocular 3D Object Detection
Jan Skvrna, Lukas Neumann
2026-09 · DOI: 10.1007/s11263-026-03007-73D Scene Generation: A Survey
Haozhe Xie, Beichen Wen, Zhaoxi Chen, Fangzhou Hong et al.
2026-09 · DOI: 10.1007/s11263-026-02999-6An Accelerated CNN System for Polyp Classification Targeting Wireless Endoscopy Images
Majdi Elhajji, Mohammed Al-Asli, Abdelkrim Zitouni
2026-09 · DOI: 10.1007/s11263-026-03030-8Disco4D: Towards Prior-Free Motion Representation Learning for Point Cloud Videos Via Self-Disentangled Contrastive Pre-Training
Zhi Zuo, Chenyi Zhuang, Pan Gao, Jie Qin et al.
2026-09 · DOI: 10.1007/s11263-026-03008-6Feed-Forward Multi-view Multi-person Reconstruction with Contrastive Human-Aware 3D Representation
Yuanwang Yang, Buzhen Huang, Zongxuan Ren, Jing Huang et al.
2026-09 · DOI: 10.1007/s11263-026-03000-0Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes
Zhaoyang Wei, Bowen Jiang, Xumeng Han, Jiashu Li et al.
2026-09 · DOI: 10.1007/s11263-026-02980-3GTA: Advancing Image-to-3D World Generation via Geometry Then Appearance Video Diffusion
Hanxin Zhu, Cong Wang, Peiyan Tu, Jiayi Luo et al.
2026-09 · DOI: 10.1007/s11263-026-02993-yE-RGB-D: Real-Time Event-Based Perception with Structured Light
Seyed Ehsan Marjani Bajestani, Giovanni Beltrame
2026-09 · DOI: 10.1007/s11263-026-03001-zWavelet-Based Adaptive Vision State Space Network for Image Harmonization
Zhaorun Zhou, Jinshan Pan, Jinhui Tang
2026-09 · DOI: 10.1007/s11263-026-02981-2Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
Bo Jiang, Shaoyu Chen, Bencheng Liao, Xingyu Zhang et al.
2026-09 · DOI: 10.1007/s11263-026-03002-yTopV-Nav: Unlocking the Top-View Spatial Reasoning Potential of MLLM for Zero-Shot Object Navigation
Linqing Zhong, Chen Gao, Zihan Ding, Yue Liao et al.
2026-09 · DOI: 10.1007/s11263-026-02996-9Variational Sign Language Translation
Rui Zhao, Liang Zhang, Biao Fu, Ruiquan Zhang et al.
2026-09 · DOI: 10.1007/s11263-026-02978-xTowards Fine-Grained Text-to-3D Quality Assessment: A Benchmark and A Two-Stage Rank-Learning Metric
Bingyang Cui, Yujie Zhang, Qi Yang, Zhu Li et al.
2026-09 · DOI: 10.1007/s11263-026-02994-xMultimodal Referring Segmentation: A Survey
Henghui Ding, Song Tang, Shuting He, Chang Liu et al.
2026-09 · DOI: 10.1007/s11263-026-02943-8P-PatchDiff: Progressive Patch Diffusion Models for Low-Light Image Enhancement
Ruoyu Guo, Haonan Zhong, Maurice Pagnucco, Yang Song et al.
2026-09 · DOI: 10.1007/s11263-026-02995-wReviews
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Version History
April 20, 2025 at 4:59 am
April 20, 2025