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CVPR 2024 Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal
This project is a deep learning image restoration tool designed to remove scratches, fading, and noise from aged photographs and film. It utilizes generative adversarial networks for image translation, alongside specialized networks for face enhancement and video colorization. The system distinguishes itself through a combination of latent-space domain mapping and progressive face enhancement to recover blurred or missing high-frequency facial details. For video content, it employs a colorization framework that uses optical flow and temporal guidance to propagate color from selected keyframes
Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön Department of Information Technology, Uppsala University
SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training
The main features of iceclear/seedvr2 are: Image Restoration, Video Restoration.
Open-source alternatives to iceclear/seedvr2 include: scott-yjyang/difftta — [CVPR 2024] Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal. microsoft/bringing-old-photos-back-to-life — This project is a deep learning image restoration tool designed to remove scratches, fading, and noise from aged… algolzw/daclip-uir — Project Page | Paper | Model Card 🤗. auroral703/pertouch. bahjat-kawar/ddrm — arXiv | PDF | Project Website. algolzw/image-restoration-sde — Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön Department of Information Technology,…