Call for Papers: Special Issue on Generative AI in 3D Vision

IEEE Transactions on Pattern Analysis and Machine Intelligence seeks submissions for this upcoming special section.
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Submissions Due: 15 August 2024

Publication: June 2025 

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


Submission Guidelines

Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the IEEE Transactions on Pattern Analysis and Machine Intelligence. All the papers will be peer-reviewed following the IEEE Transactions on Pattern Analysis and Machine Intelligence reviewing procedures. The manuscripts should be submitted here.


Contact the Lead Guest Editor at

  • Deqing Sun (Lead Guest Editor)Senior Staff Research Scientist, Google
  • Xiangyu Xu, Professor, Xi’an Jiaotong University
  • Siyu Tang, Assistant Professor, ETH Zurich
  • Angela Dai, Assistant Professor, Technical University of Munich
  • Jiajun Wu, Assistant Professor, Stanford University
  • Katerina Fragkiadaki, Associate Professor, Carnegie Mellon University
  • Andrea Tagliasacchi, Associate Professor, Simon Fraser University; Research Scientist, DeepMind
  • Christian Theobalt, Professor, Max Planck Institute for Informatics; Saarland University
  • Ming-Hsuan Yang, Professor, University of California, Merced; Research Scientist, Google