AI-Driven Multimodal Image and Video Processing: Advances and Applications

Dear Colleagues,

The integration of artificial intelligence (AI) and multimodal data has revolutionized image and video processing, enabling breakthroughs that transcend the limitations of single-modality and traditional rule-based methods. AI techniques, from deep learning and large-scale pretraining to generative models and self-supervised learning, empower the fusion of heterogeneous data streams (e.g., RGB, depth, thermal, textual, audio, sensor, and physiological signals) to unlock unprecedented robustness, accuracy, and generalizability in visual analysis.

This Special Issue aims to showcase cutting-edge advances in AI-driven multimodal image and video processing, spanning foundational technologies (e.g., cross-modal fusion architectures, representation learning, and generative AI for visual media) and transformative real-world applications across healthcare, metaverses, education, autonomous systems, smart cities, media, remote sensing, and beyond. We seek to bring together researchers, engineers, and practitioners from academia, industry, and research institutions to share innovative findings, exchange interdisciplinary insights, and accelerate the translation of AI–multimodal synergies into practical solutions. By bridging theory and application, this issue will serve as a definitive platform for shaping the future of visual intelligence in an increasingly multimodal world.

Dr. Fangli Ying
Dr. Liting Zhou
Prof. Dr. Cathal Gurrin
Dr. Jianhua Li
Guest Editors

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