Trends and Prospects in Image/Video Generation Technologies
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electronic Multimedia".
Deadline for manuscript submissions: 15 May 2026 | Viewed by 75
Special Issue Editors
Interests: multi-view video coding; view synthesis; depth image-based rendering; high-efficiency video coding; video transcoding; image processing; machine learning; deep learning
Interests: multimodal/multi-view clustering; weakly-supervised and self-supervised learning; graph machine learning; low-light image enhancement; underwater image enhancement
Special Issue Information
Dear Colleagues,
With remarkable advancements in deep learning, particularly in generative models such as diffusion models, generative adversarial networks (GANs), and autoregressive transformers, the field of image and video generation is undergoing a revolution. These technologies have dramatically enhanced the capability to create high-fidelity, diverse, and controllable visual content, pushing the boundaries of what is possible. This progress is significant as it fuels innovation across a wide spectrum of applications, from film production, game development, and virtual reality to architectural visualization, data augmentation for training robust AI systems, and even therapeutic and artistic expression. The ability to generate realistic and meaningful visual data efficiently is becoming a cornerstone of modern digital technology.
We are pleased to invite you to contribute to this Special Issue, which seeks to capture the cutting-edge developments and chart the future trajectory of image and video generation technologies.
This Special Issue aims to provide a platform for researchers and practitioners to share novel algorithms, insightful methodologies, and innovative applications that address the current challenges and explore new opportunities in this rapidly evolving domain. We hope to foster discussions on improving the quality, efficiency, controllability, and ethical deployment of generative models.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Advanced generative models for image and video synthesis (e.g., diffusion models, GANs, VAEs, flow-based models);
- Controllable generation and editing techniques, including text-to-image/video, style transfer, and semantic manipulation;
- High-resolution and long-term coherent video generation and prediction;
- Efficient generation methods, including model compression, distillation, and fast sampling techniques;
- Multi-modal generation and cross-modal translation (e.g., audio to video, sketch to image)；
- 3D-aware and 4D scene generation for virtual and augmented reality;
- Generative models for scientific visualization and medical imaging；
- Ethical considerations, bias mitigation, deepfake detection, and responsible deployment of generation technologies；
- Novel applications in content creation, design, entertainment, and simulation.
We look forward to receiving your contributions.
Dr. Linwei Zhu
Dr. Wenhui Wu
Dr. Huan Zhang
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- image/video generation
- generative models
- diffusion models
- controllable generation
- deepfakes
- text-to-image synthesis
- ethical AI
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