ISNAS-DIP
ISNAS-DIP: Image Specific Neural Architecture Search for Deep Image Prior [CVPR 2022]
File Explorer
- models.csv
- method.jpg
- metod.pdf
- f16_512_rgb.png
- monar_256.png
- woman_rgb.png
- __init__.py
- common.py
- common_test.py
- cross_skip.py
- downsampler.py
- gen_upsample_layer.py
- model_denoising.py
- model_inpainting.py
- model_sr.py
- ref.py
- resnet.py
- skip.py
- skip_search_up.py
- texture_nets.py
- unet.py
- unet_search_up.py
- demo.py
- gen_id.py
- gen_upsample_layer-prev.py
- gen_upsample_layer.py
- genotypes-prev.py
- genotypes.py
- index_to_model_mapping.log
- model.py
- model_gen.py
- operations-prev.py
- operations.py
- utils.py
- bestiters.ipynb
- correlations.ipynb
- histograms.ipynb
- nb_utils.py
- qualitative_comparisons.ipynb
- models_generated.lst
- matcher.py
- perceptual_loss.py
- vgg_modified.py
- array_utils.py
- basic_utils.py
- common_types.py
- common_utils.py
- data_structures.py
- denoising_utils.py
- feature_inversion_utils.py
- funcs.py
- gpu_utils.py
- image_utils.py
- inpainting_utils.py
- keywords.py
- load_image.py
- masks.py
- matcher.py
- metric_utils.py
- model_utils.py
- paths.py
- paths_old.py
- selection.py
- sr_utils.py
- timer.py
- .gitignore
- calculate_lowpass_metrics.py
- calculate_similarity_metrics.py
- concatenate_random_outputs.py
- create_noisy_images.py
- create_random_outputs.py
- denoising.py
- denoising.sh
- dip.py
- dip.sh
- inpainting.py
- inpainting.sh
- isnasdip.sh
- LICENSE
- lowpass_metrics.lst
- models_generated.lst
- nasdip.py
- nasdip.sh
- other_metrics.lst
- random_search.py
- README.md
- README.txt
- remove_alpha.py
- requirements.txt
- similarity_metrics.lst
- sr.py
- sr.sh
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conda create
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