11 open-source projects similar to jbhuang0604/structcompletion, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best StructCompletion alternative.
Lama is an image restoration framework and deep learning model designed for image inpainting and object removal. It provides the tools necessary to train and evaluate neural networks that fill masked areas and repair corrupted visual data. The system utilizes a Fourier convolution neural network to maintain global image structure and reconstruct periodic patterns. This architecture allows for resolution-independent inference, enabling the processing of high-resolution images without increasing memory or computational requirements. The project includes a synthetic dataset generator that creat
Keras-GAN is a collection of generative adversarial network implementations built with Keras for synthetic data generation and image manipulation. It provides frameworks for image-to-image translation, image inpainting, and neural image super-resolution. The library includes tools for learning disentangled latent space representations to control specific attributes of synthetic outputs. It also features capabilities for image domain translation using paired or unpaired data and the ability to fill corrupted or missing image parts by analyzing surrounding visual context. The project covers ge
GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and deep learning inference engine, providing programmatic access to a wide range of algorithms for image manipulation, object detection, and video analysis. The project differentiates itself through high-performance native bindings and hardware acceleration. It utilizes a foreign function interface to map Go calls to C++ functions and includes a hardware-agnostic backend dispatch to route neural network tasks to computation engines such as CUDA and OpenVINO. The library covers a br
ArXiv | BibTex We develop a new approach for image inpainting that does a better job of reproducing filled regions exhibiting fine details inspired by our understanding of how artists work: lines first, color next. We propose a two-stage adversarial model EdgeConnect that comprises of an edge…
High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis
CVPR 2016 Unsupervised Feature Learning by Image Inpainting using GANs
This is the official impelmenation of the paper Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models.
Matcaffe implementation of our CVPR17 paper on face completion.
Inpainting using Denoising Diffusion Probabilistic Models
Image Completion with Deep Learning in TensorFlow