an inference framework for image/video restoration with VapourSynth support
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Updated
Oct 6, 2024 - Python
an inference framework for image/video restoration with VapourSynth support
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🍷 A Convenience Multi-Upscalers for Video, Images. Batch Processing, Multithreaded
Misc; latest version of waifu2x; 2D video to stereo 3D video conversion
This code uses power of residual connections to train a 54 layer recursive network for image superesolution task
Deep learning training framework for image super resolution and restoration.
neosr is a framework for training real-world single-image super-resolution networks.
The official PyTorch implementation for Learning Truncated Causal History Model for Video Restoration, accepted to NeurIPS 2024.
Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]
PyTorch library for solving imaging inverse problems using deep learning
Torch implementation of EDSR, a model based on Residual Blocks for Super Resolution
A collection of tools for painting super-resolution images
FMBoost: Boosting Latent Diffusion with Flow Matching (ECCV 2024 Oral)
Explore Super Image Resolution through sophisticated degradation modeling. Explore this approach to enhance real image quality and elevate your image enhancement capabilities
Machine Learning - Super Resolution
Implementation of the paper "Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data." 🖼️
Unreal Real-Time Super Resolution (URTSR) is a neural rendering method for highly efficient real-time rendering super resolution.
BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical Flow
ImSwitch is a software solution in Python that aims at generalizing microscope control by providing a solution for flexible control of multiple microscope modalities.
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