From Visual Perception to Spatiotemporal Understanding
A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Computer Vision and Pattern Recognition".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 99
Special Issue Editors
Interests: computer vision; spatial intelligence; robot vision
Special Issue Information
Dear Colleagues,
Advances in sensing, computing and learning are reshaping how machines perceive and reason about the physical world. Spatial AI has become a unifying direction that connects image and video understanding with 3D geometry, temporal dynamics and interaction, enabling progress in robotics, autonomous systems, digital twins, AR and VR, remote sensing, medical imaging and intelligent surveillance. This Special Issue provides a broad forum for recent developments and future trends in spatial AI for image and video understanding, with a focus on methods that learn, infer and leverage spatial and spatiotemporal structure from visual data.
We welcome contributions across the full spectrum of vision research, from image and video enhancement that supports downstream spatial reasoning to higher level tasks such as 3D scene understanding, dynamic scene modeling and spatially grounded recognition. Submissions on multi sensor and multi modal perception are encouraged, including fusion of RGB with depth, LiDAR, event streams, thermal imagery and other modalities. We also invite work on efficient and deployable spatial perception systems, robust learning under distribution shifts and reliable evaluation through datasets, benchmarks and metrics. In addition to methodological advances, application-driven studies that demonstrate spatial intelligence in real world scenarios are highly welcome.
Dr. Ruyu Liu
Prof. Dr. Yongwei Miao
Guest Editors
Manuscript Submission Information
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Keywords
- spatial AI
- spatial intelligence
- 3D vision
- 4D scene understanding
- depth estimation
- multi-view learning
- neural reconstruction
- SLAM
- egocentric vision
- multi-modal perception
- sensor fusion
- 3D-aware generative models
- world models
- embodied perception
- visual navigation
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