Ne2Ne-Image-Denoising
policy-adaptation-during-deployment
| Ne2Ne-Image-Denoising | policy-adaptation-during-deployment | |
|---|---|---|
| 1 | 1 | |
| 27 | 109 | |
| - | - | |
| 3.0 | 1.8 | |
| 11 months ago | over 3 years ago | |
| Python | Python | |
| - | - |
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Ne2Ne-Image-Denoising
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Neighbour2Neighbour: The new self-supervised Image Denoising training
It gives outstanding denoising performance with just 300 training images. Have a look at these image results and minimal network implementation here: https://github.com/neeraj3029/Ne2Ne-Image-Denoising
policy-adaptation-during-deployment
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Exploring Self-Supervised Policy Adaptation To Continue Training After Deployment Without Using Any Rewards
Code: https://github.com/nicklashansen/policy-adaptation-during-deployment
What are some alternatives?
SwinIR - SwinIR: Image Restoration Using Swin Transformer (official repository)
envpool - C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
byol-pytorch - Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
simsiam-cifar10 - Code to train the SimSiam model on cifar10 using PyTorch
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
lightly - A python library for self-supervised learning on images.
drl_grasping - Deep Reinforcement Learning for Robotic Grasping from Octrees
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
dmc2gymnasium - Gymnasium integration for the DeepMind Control (DMC) suite