[Call for Paper] IEEE ICME 2023 Workshop on 3D Multimedia Analytics, Search and Generation
https://3dmm-icme2023.github.io/

OVERVIEW
Today, ubiquitous multimedia sensors and large-scale computing infrastructures are producing at a rapid velocity of 3D multi-modality data, such as 3D point cloud acquired with LIDAR sensors, RGB-D videos recorded by Kinect cameras, meshes of varying topology, and volumetric data. 3D multimedia combines different content forms such as text, audio, images, and video with 3D information, which can perceive the world better since the real world is 3-dimensional instead of 2-dimensional. For example, the robots can manipulate objects successfully by recognizing the object via RGB frames and perceiving the object size via point cloud. Researchers have strived to push the limits of 3D multimedia search and generation in various applications, such as autonomous driving, robotic visual navigation, smart industrial manufacturing, logistics distribution, and logistics picking. The 3D multimedia (e.g., the videos and point cloud) can also help the agents to grasp, move and place the packages automatically in logistics picking systems. Therefore, 3D multimedia analytics is one of the fundamental problems in multimedia understanding. Different from 3D vision, 3D multimedia analytics mainly concentrate on fusing the 3D content with other media. It is a very challenging problem that involves multiple tasks such as human 3D mesh recovery and analysis, 3D shapes and scenes generation from real-world data, 3D virtual talking head, 3D multimedia classification and retrieval, 3D semantic segmentation, 3D object detection and tracking, 3D multimedia scene understanding, and so on. Therefore, the purpose of this workshop is to: 1) bring together the state-of-the-art research on 3D multimedia analysis; 2) call for a coordinated effort to understand the opportunities and challenges emerging in 3D multimedia analysis; 3) identify key tasks and evaluate the state-of-the-art methods; 4) showcase innovative methodologies and ideas; 5) introduce interesting real-world 3D multimedia analysis systems or applications; and 6) propose new real-world or simulated datasets and discuss future directions. We solicit original contributions in all fields of 3D multimedia analysis that explore the multi-modality data to generate the strong 3D data representation. We believe this workshop will offer a timely collection of research updates to benefit researchers and practitioners in the broad multimedia communities.

We invite submissions for ICME 2023 Workshop, 3D Multimedia Analytics, Search and Generation (3DMM2023), which brings researchers together to discuss robust, interpretable, and responsible technologies for 3D multimedia analysis. We solicit original research and survey papers that must be no longer than 6 pages (including all text, figures, and references). Each submitted paper will be peer-reviewed by at least three reviewers. All accepted papers will be presented as either oral or poster presentations, with the best paper award. Papers that violate anonymity, do not use the ICME submission template will be rejected without review. By submitting a manuscript to this workshop, the authors acknowledge that no paper substantially similar in content has been submitted to another workshop or conference during the review period. Authors should prepare their manuscript according to the Guide for Authors of ICME.

The scope of this workshop includes, but is not limited to, the following topics:
Generative Models for 3D Multimedia and 3D Multimedia Synthesis
Generating 3D Multimedia from Real-world Data
3D Multimodal Analysis and Description
Multimedia Virtual/Augmented Reality
3D Multimedia Systems
3D Multimedia Search and Recommendation
Mobile 3D Multimedia
3D Shape Estimation and Reconstruction
3D Scene and Object Understanding
High-level Representation of 3D Multimedia Data
3D Multimedia Application in Industry

Organizers
• Shan An, JD Health International Inc., Beijing, China
• An-An Liu, Tianjin University, Tianjin, China
• Kun Liu, JD Logistics Inc., Beijing, China
• Na Zhao, Singapore University of Technology and Design, Singapore
• Guoxin Wang, Zhejiang University, Hangzhou, China
• Wu Liu, JD Explore Academy, Beijing, China
• Antonios Gasteratos, Democritus University of Thrace, Greece