Projects in Awesome Lists tagged with pix2pix-tensorflow

https://github.com/datitran/face2face-demo

pix2pix demo that learns from facial landmarks and translates this into a face

Last synced: 08 Apr 2025

https://github.com/memo/webcam-pix2pix-tensorflow

Source code and pretrained model for running pix2pix in realtime on a webcam feed.

ai-art aiart artificial-intelligence artificial-neural-networks deep-learning deep-neural-networks pix2pix pix2pix-tensorflow tensorflow

Last synced: 09 Apr 2025

https://github.com/pubkey/fashion-segmentation

A tensorflow model for segmentation of fashion items out of multiple product images

clothes-retrieval computer-vision deep-learning fashion fashion-ai fashion-mnist fashionai image-segmentation pix2pix pix2pix-tensorflow segmentation vision-for-fashion

Last synced: 30 Apr 2025

https://github.com/adriacabeza/human-extractor

:bust_in_silhouette: Cutting people out automatically using Image translation's architecture Pix2Pix

adversarial-machine-learning computer-vision gan google-colab pix2pix pix2pix-tensorflow python retodotcsv2080super tensorflow tensorflow-2

Last synced: 30 Apr 2025

https://github.com/adriacabeza/Human-Extractor

:bust_in_silhouette: Cutting people out automatically using Image translation's architecture Pix2Pix

adversarial-machine-learning computer-vision gan google-colab pix2pix pix2pix-tensorflow python retodotcsv2080super tensorflow tensorflow-2

Last synced: 14 Mar 2025

https://github.com/gsurma/mono_depth_estimator

Mono depth estimation for self-driving cars 🚗

ai artificial-intelligence computer-graphics computer-vision deep-learning depth-estimation depth-prediction gan image-to-image-translation jupyter-notebook keras machine-learning mono-depth pix2pix pix2pix-tensorflow python self-driving-car stereo-matching stereo-vision

Last synced: 12 May 2025

https://github.com/fitushar/study-of-low-dose-to-high-dose-ct-using-supervised-learning-with-gan-and-virtual-imaging-trials

Computed tomography (CT) is one of the most widely used radiography exams worldwide for different diagnostic applications. However, CT scans involve ioniz- ing radiational exposure, which raises health concerns. Counter-intuitively, low- ering the adequate CT dose level introduces noise and reduces the image quality, which may impact clinical diagnosis. This study analyzed the feasibility of using a conditional generative adversarial network (cGAN) called pix2pix to learn the mapping from low dose to high dose CT images under different conditions. This study included 270 three-dimensional (3D) CT scan images (85,050 slices) from 90 unique patients imaged virtually using virtual imaging trials platform for model development and testing. Performance was reported as peak signal-to-noise ra- tio (PSNR) and structural similarity index measure (SSIM). Experimental results demonstrated that mapping a single low-dose CT to high-dose CT and weighted two low-dose CTs to high-dose CT have comparable performances using pix2pix CGAN and applicability of using VITs

ct deep-learning denoising gan generative-adversarial-network pix2pix pix2pix-tensorflow