├── LICENSE ├── README.md ├── data ├── NYUtrain.txt ├── NYUval.txt └── test.txt ├── depth_uncrop.py ├── depth_upsample.py ├── diverse_estimation.py ├── example ├── figure.jpg ├── inputs │ ├── 00959_crop120x160.png │ ├── 00959_f.png │ ├── 00959_i.png │ ├── 00959_lowres48x.png │ ├── 00959_pairs.txt │ └── 00959_sparseN100.png └── outputs │ ├── 00959_adversary.png │ ├── 00959_diverse_best.png │ ├── 00959_gt.png │ ├── 00959_guided_sparse100.png │ ├── 00959_guideds2d.png │ ├── 00959_interactive_best.png │ ├── 00959_mean.png │ ├── 00959_oracle.png │ ├── 00959_s2d.png │ ├── 00959_uncertainty.png │ ├── 00959_uncropped.png │ └── 00959_upsampled.png ├── guided_sampling.py ├── interactive_estimation.py ├── ordinal_estimation.py ├── prdepth ├── __init__.py ├── dataset.py ├── environment.yml ├── metric.py ├── net │ ├── DORN.py │ ├── ResNet101.py │ ├── VAE.py │ ├── __init__.py │ ├── base.py │ └── net.py ├── optimization │ ├── __init__.py │ ├── interactive_optimizer.py │ ├── s2d_optimizer.py │ └── uncrop_optimizer.py ├── sampler.py ├── tf_extract_grad.py └── utils.py ├── scripts └── download_models.sh ├── sparse_to_dense.py ├── test_VAE.py └── train_VAE.py /LICENSE: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/likesum/prdepth/HEAD/LICENSE -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/likesum/prdepth/HEAD/README.md -------------------------------------------------------------------------------- /data/NYUtrain.txt: -------------------------------------------------------------------------------- 1 | path-to-NYUv2/kitchen_0031/00581 2 | -------------------------------------------------------------------------------- /data/NYUval.txt: -------------------------------------------------------------------------------- 1 | path-to-NYUv2/classroom_0004/00031 2 | 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