AI Article Synopsis
- Vehicles face various road obstacles that can't all be pre-recorded for detector training.
- To tackle this, researchers choose specific image sections and fill them in with the surrounding road texture to hide the obstacles.
- A specialized neural network is then used to identify differences between the original and modified images, indicating whether an obstacle has been removed.
Article Abstract
Vehicles can encounter a myriad of obstacles on the road, and it is impossible to record them all beforehand to train a detector. Instead, we select image patches and inpaint them with the surrounding road texture, which tends to remove obstacles from those patches. We then use a network trained to recognize discrepancies between the original patch and the inpainted one, which signals an erased obstacle.
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| http://dx.doi.org/10.1109/TPAMI.2023.3335152 | DOI Listing |
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