alexklwong/augundo
PyTorch Implementation of AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation (ECCV 2024)
This project helps researchers and engineers in computer vision accurately determine depth from single images. It takes raw image data, often from datasets like KITTI or NYUv2, and processes it to output precise depth maps. Professionals working on 3D reconstruction, autonomous navigation, or augmented reality applications would find this beneficial.
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Use this if you need to improve the accuracy of monocular depth estimation or completion models using advanced data augmentation techniques.
Not ideal if you are looking for a plug-and-play solution without needing to set up datasets or train models within a Python/PyTorch environment.
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Language
Python
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Last pushed
Aug 09, 2025
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