About this Research Topic
With significant recent developments in 3D sensors, large-scale 3D geometry datasets, and advances in 3D deep learning, 3D computer vision plays an increasingly important role in numerous domains. This includes a varied range of cutting-edge applications spanning robotics, autonomous navigation and localization, 3D scene reconstruction, 3D scene understanding, 3D tracking and surveillance, digital city modeling, and virtual and augmented reality.
The goal of this Research Topic is to present high-quality research on 3D computer vision that addresses challenging problems in 3D data processing, proposes new developments for reliable 3D data acquisition, and advances the state of the art in 3D applications.
This Research Topic encourages researchers to investigate and develop various aspects relating to recent advances in 3D computer vision. Topics of interest include (but are not limited to):
- 3D analysis and modeling (3D deep learning and 3D machine learning, 3D recognition, 3D Segmentation, S3D detection, 3D registration)
- 3D acquisition (calibration, structure from motion and SLAM, computational photography, 3D reconstruction)
- 3D applications (robotics, medical applications, sports applications, digital fabrication)
Keywords: 3D Computer Vision, 3D Analysis, 3D Modeling, 3D Acquisition, 3D Applications, 3D Vision Learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.