Advances in Vision-Based 3D Reconstruction
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 October 2026
Special Issue Editor
Special Issue Information
Dear Colleagues,
Vision-based 3D reconstruction remains a cornerstone of computer vision, with applications spanning autonomous systems, digital twins, cultural heritage, and beyond. Recent advances are transforming established pipelines: foundation models (DINOv2, SAM, and CLIP) now provide robust priors for feature extraction and scene understanding, while agentic AI workflows automate complex reconstruction tasks from image acquisition to quality assessment.
This Special Issue seeks contributions advancing the state of the art in vision-based 3D reconstruction. Topics of interest include structure-from-motion and multi-view stereo enhancements; foundation models for geometric and semantic feature learning; point cloud generation, processing, and conversion to 3D Gaussian splatting; semantic-aware reconstruction integrating segmentation, scene graphs, and language grounding; diffusion models for 3D completion and novel view synthesis; and agentic pipelines orchestrating end-to-end reconstruction with minimal supervision.
We welcome submissions addressing key challenges including scalability to large-scale environments, generalization across domains, uncertainty quantification, and fusion with complementary sensors such as LiDAR. Both methodological innovations and application-driven studies are encouraged, particularly those bridging the gap between research and deployment. This Special Issue aims to showcase how emerging AI paradigms—such as foundation models, neural representations, and autonomous workflows—are reshaping 3D reconstruction into a more robust, semantic-rich, and accessible discipline.
Prof. Dr. Florent Poux
Guest Editor
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Keywords
- 3D reconstruction
- SLAM
- photogrammetry
- foundation models
- 3D Gaussian Splatting
- point cloud processing
- semantic reconstruction
- agentic AI
- structure-from-motion
- neural scene representations
- vision-language models
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