Models for the paper Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth Estimation (CoLLAs 2024) by Amir El-Ghoussani, Julia Hornauer, Gustavo Carneiro and Vasileios Belagiannis. Code: github.com/AmirMaEl/SemiSupMDE. A single U-Net (54.6M parameters) predicts depth from one RGB image. It is trained on synthetic Virtual KITTI with ground truth and adapted to real KITTI without any KITTI labels, using a pairwise loss on source images and a perturbation-consistency loss across RandAugment views of the unlabelled target images. Both checkpoints are PyTorch state dicts. KITTI Eigen test split (697 images), Garg crop, velodyne ground truth, no median scaling: With…
Independent publisher
Amir El-Ghoussani
AmirMaEl
Models in Library1
Datasets in Library0
Models on Hugging Face1
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Published tasks: Depth estimation.
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