IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) publishes articles on all traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence, with a particular emphasis on machine learning for pattern analysis. Areas such as techniques for visual search, document and handwriting analysis, medical image analysis, video and image sequence analysis, content-based retrieval of image and video, face and gesture recognition and relevant specialized hardware and/or software architectures are also covered.

Special Issue on Generative AI in 3D Vision
Submission Date: 2024-08-15

The rapid advancement of Generative AI (GenAI) in 3D computer vision is driving transformative changes across a variety of fields such as virtual and augmented reality, gaming, film production, computer-aided design, and the emerging Metaverse. These technologies are not only enhancing the way we create and interact with digital content but are also setting the stage for more realistic, dynamic, and immersive user experiences.

This special issue seeks to foster breakthroughs and address critical problems within this domain. By bringing together researchers and practitioners to share their insights and research findings, we aim to pave the way for the next generation of 3D GenAI technologies and applications.

The topics of this special issue include, but are not limited to:

    Advances in 3D generative models, such as GANs, VAEs, Autoregressive models, Diffusion models, Normalizing Flow, etc.
    Innovations in 3D representations for GenAI, such as point clouds, meshes, voxels, neural fields, Gaussian splatting, multiplane images, etc.
    3D reconstruction from single or sparse views
    Novel view synthesis
    3D human generation, reconstruction, and animation
    3D from multi-modality, such as text, audio, etc.
    Multi-view image generation from multi-modality, such as text, audio, etc.
    4D (dynamic) generation and reconstruction
    3D scene/object manipulation, such as instruction-based editing, drag-based editing, multi-object interaction, style transfer, etc.
    Applications of 3D generative models in fields like virtual/augmented reality, gaming, film production, computer-aided design, Metaverse, robotics, and embodied AI
    Large-scale 3D datasets
    Evaluation metrics and benchmarks for 3D generative models
    Efficiency and scalability of 3D generative models
    Robustness and security of 3D generative models