Summary of Fusionvision: a Comprehensive Approach Of 3d Object Reconstruction and Segmentation From Rgb-d Cameras Using Yolo and Fast Segment Anything, by Safouane El Ghazouali et al.
FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything
by Safouane El Ghazouali, Youssef Mhirit, Ali Oukhrid, Umberto Michelucci, Hichem Nouira
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces FusionVision, a pipeline for robust 3D object segmentation in RGB-D imagery. It addresses the limitations of traditional computer vision systems by merging state-of-the-art object detection and instance segmentation techniques. The pipeline employs YOLO for object detection in the RGB image domain and FastSAM for semantic segmentation, producing refined segmentation masks. The synergy between these components enables a cohesive fusion of object detection and segmentation, enhancing overall precision. FusionVision is evaluated on various benchmarks, including the Matterport3D dataset. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary FusionVision is a new way to understand 3D scenes by combining information from color (RGB) and depth images. Currently, computer vision systems struggle to accurately detect objects in these types of images. The authors created FusionVision to solve this problem by using two powerful tools: YOLO for object detection and FastSAM for segmentation. This combination helps identify what’s in the scene and where it is. The results are more accurate than previous methods, making it a useful tool for many applications. |
Keywords
» Artificial intelligence » Instance segmentation » Object detection » Precision » Semantic segmentation » Yolo
