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This project deciphers if we can bake smooth latent space properties into the inherent pose estimation model of unsupervised/semi-supervised monocular depth estimation models.

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Name		Name	Last commit message	Last commit date
Latest commit History 106 Commits
.dvc		.dvc
configs		configs
docker		docker
geometry		geometry
images		images
models		models
notes		notes
pretrained		pretrained
pseudo-lidar		pseudo-lidar
splits		splits
utils		utils
.dvcignore		.dvcignore
.gitignore		.gitignore
README.md		README.md
dataloaders.py		dataloaders.py
evaluate.py		evaluate.py
inference.py		inference.py
losses.py		losses.py
prep_split_files.py		prep_split_files.py
run_training_pipeline.sh		run_training_pipeline.sh
train.py		train.py
trainer.py		trainer.py

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unsupervised-pseuso-LiDAR

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This project deciphers if we can bake smooth latent space properties into the inherent pose estimation model of unsupervised/semi-supervised monocular depth estimation models.

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