Journal Information
International Journal of Computer Vision (IJCV)
Impact Factor:
Call For Papers
The International Journal of Computer Vision (IJCV) provides a forum for the dissemination of new research results in the rapidly growing field of computer vision. Now publishing 15 issues a year, International Journal of Computer Vision presents high-quality, original contributions to the science and engineering of this rapidly growing field.

Regular articles (up to 25 journal pages) present major technical advances of broad general interest.
Short articles (up to 10 pages) provide a fast publication path for novel research results.
Survey articles (up to 30 pages) offer critical reviews of the state of the art and/or tutorial presentations of pertinent topics.
Book reviews, position papers, and editorials by leading scientific figures will from time to time complement the technical content of the journal.
Additional, on-line material such as still images and video sequences, data sets, and software is encouraged.

Papers should cover:

Mathematical, physical and computational aspects of computer vision: image formation, processing, analysis, and interpretation; machine learning techniques; statistical approaches; sensors.
Applications: image-based rendering, computer graphics, robotics, photo interpretation, image retrieval, video analysis and annotation, multi-media, medicine, human-machine interaction, surveillance.
Connections with human perception: computational and architectural aspects of human vision.


There are no page charges in IJCV.
Papers are published on line in advance of print publication.
Responses to position papers are welcome.
Editorials, position papers, and their responses will be available online free of charge.
IJCV has a liberal copyright policy.

Academic and industrial researchers in computer vision, robotics, and artificial intelligence, as well as psychologists and neuroscientists interested in the connection between computer and human vision, will find IJCV to be the essential forum for important results in the field.
Last updated by Dou Sun in 2022-01-29
Special Issues
Special Issue on Large-Scale Generative Models for Content Creation and Manipulation
Submission Date: 2024-02-28

The field of computer vision has witnessed significant advancements in recent years, largely due to the remarkable progress made in generative models. Large-scale generative models have emerged as a powerful tool for content creation and manipulation, revolutionizing the way visual content is generated and modified. These models have demonstrated their ability to generate high-quality images, videos, and 3D models, while also enabling diverse content manipulation tasks such as style transfer, image inpainting, and object manipulation. The advent of large-scale generative models has opened up new possibilities for content creation and manipulation, offering unprecedented control over visual elements and fostering innovation across a wide range of applications. Large-scale generative models leverage sophisticated architectures, such as generative adversarial networks (GANs), variational autoencoders (VAEs), diffusion models, and flow-based models, to synthesize visually appealing and realistic content. They tackle the challenges posed by generating high-resolution and diverse images and videos, incorporating temporal consistency and coherence for video generation, and enabling the creation of immersive content for applications like virtual reality and entertainment. Moreover, these models facilitate content manipulation by enabling style transfer, where the visual characteristics of one image or video are transferred to another, image and video inpainting for filling missing or corrupted regions seamlessly, and object manipulation for removing, adding, or rearranging objects within visual scenes. Additionally, large-scale generative models have extended their capabilities to 3D content manipulation, encompassing tasks such as shape generation, texture synthesis, and deformation. The development and exploration of large-scale generative models for content creation and manipulation present exciting opportunities to transform the way we generate and modify visual content. Scope This special issue invites original research articles and reviews focusing on large-scale generative models for content creation and manipulation. The topics of interest include, but are not limited to: 1. Large-scale generative models for 2D/3D image and video synthesis: - Advanced architectures and training techniques for generating high-resolution and diverse images and videos. -Temporal consistency and coherence in video generation. -Novel applications in content synthesis, virtual reality, and entertainment. 2. Content manipulation using large-scale generative models: -Style transfer for artistic rendering, domain adaptation, and visual effects. -Image and video inpainting for filling missing or corrupted regions. -Object manipulation, removal, and rearrangement in images and videos. -3D content manipulation, including shape generation, texture synthesis, and deformation. 3. Training and optimization of large-scale generative models: -Scalable training strategies for handling large datasets and complex generative models. -Regularization and regularization techniques for improving training stability and convergence. -Model compression and acceleration for efficient deployment and real-time applications. 4. Evaluation and benchmarking of large-scale generative models: -Metrics and protocols for assessing the quality and diversity of generated content. -Comparative studies and analysis of different large-scale generative models. -Evaluation on challenging datasets and benchmarks for content creation and manipulation tasks. 5. Applications and impact of large-scale generative models: -Content creation and enhancement in areas such as digital art, design, and advertising. -Content manipulation for data augmentation, data synthesis, and virtual reality applications. -Ethical considerations and challenges related to large-scale generative models. Important Dates: Manuscript submission deadline: February 28, 2024 First review notification: May 31, 2024 Revised manuscript submission: July 31, 2024 Final review notification: September 30, 2024 Final manuscript submission: October 31, 2024 Publication date: December 31, 2024
Last updated by Dou Sun in 2023-09-19
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Full NameImpact FactorPublisher
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