Car Damage Detection and Patch-to-Patch Self-supervised Image Alignment

Hanxiao Chen
3/11/2024
cs.CVcs.AI

No official code found. Best implementation: 2000222/Car-Damage-DetectionV0 (10 stars, last commit 2024-07-17).

Abstract

Most computer vision applications aim to identify pixels in a scene and use them for diverse purposes. One intriguing application is car damage detection for insurance carriers which tends to detect all car damages by comparing both pre-trip and post-trip images, even requiring two components: (i) car damage detection; (ii) image alignment. Firstly, we implemented a Mask R-CNN model to detect car damages on custom images. Whereas for the image alignment section, we especially propose a novel self-supervised Patch-to-Patch SimCLR inspired alignment approach to find perspective transformations between custom pre/post car rental images except for traditional computer vision methods.

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Code Implementations(1)

2000222/Car-Damage-DetectionV0Community100%

AI methods for Car Damage Detection with Mask-RCNN

102Python, Jupyter NotebookJun 28, 20202 years ago
car-damage-detection

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Cite this paper

@article{chen2024damage,
  title  = {Car Damage Detection and Patch-to-Patch Self-supervised Image Alignment},
  author = {Hanxiao Chen},
  year   = {2024},
  eprint = {2403.06674},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.06674v1}
}

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