Papers with Code 아카이브
Image Denoising
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Image Denoising is a computer vision task that involves removing noise from an image. Noise can be introduced into an image during acquisition or processing, and can reduce image quality and make it difficult to interpret. Image denoising techniques aim to restore an image to its original quality by reducing or removing the noise, while preserving the important features of the image.
<span style="color:grey; opacity: 0.6">( Image credit: Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sherbret/lichi
공식 코드Linear Combinations of Patches are Unreasonably Effective for Single-Image Denoising
https://github.com/sherbret/nl-ridge
공식 코드Towards a unified view of unsupervised non-local methods for image denoising: the NL-Ridge approach
https://github.com/sherbret/normalization_equivariant_nn
공식 코드Normalization-Equivariant Neural Networks with Application to Image Denoising
https://github.com/shlee0/noisetransfer
공식 코드NoiseTransfer: Image Noise Generation with Contrastive Embeddings
https://github.com/shuangxu96/pwrctv
공식 코드https://github.com/shurenqi/fmr
공식 코드https://github.com/sijang/spachtransformer
공식 코드https://github.com/sonyresearch/raw_image_denoising
공식 코드https://github.com/srameo/led
공식 코드Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model
https://github.com/sreyas-mohan/udvd
공식 코드https://github.com/sssohrab/PhDthesis
공식 코드Learning to compress and search visual data in large-scale systems
https://github.com/stephen0808/dnlut
공식 코드DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup Tables
https://github.com/sulam-group/k-rcps
공식 코드How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control
https://github.com/summitgao/hcanet
공식 코드Hybrid Convolutional and Attention Network for Hyperspectral Image Denoising
https://github.com/summitgao/mafnet
공식 코드Multi-scale Adaptive Fusion Network for Hyperspectral Image Denoising
https://github.com/sunke123/FW-Net
공식 코드Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse Coding
https://github.com/swz30/CycleISP
공식 코드CycleISP: Real Image Restoration via Improved Data Synthesis
https://github.com/swz30/MIRNet
공식 코드Learning Enriched Features for Real Image Restoration and Enhancement
https://github.com/swz30/MPRNet
공식 코드https://github.com/swz30/mirnetv2
공식 코드Learning Enriched Features for Fast Image Restoration and Enhancement
https://github.com/swz30/restormer
공식 코드Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/sybernix/icassp24-joint
공식 코드Mixed Graph Signal Analysis of Joint Image Denoising / Interpolation
https://github.com/sypsyp97/Filter2Noise
공식 코드https://github.com/tacalvin/Poisson2Sparse
공식 코드Poisson2Sparse: Self-Supervised Poisson Denoising From a Single Image
https://github.com/takuhirok/NR-GAN
공식 코드https://github.com/terryoo/AINDNet
공식 코드Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization
https://github.com/tetsuyaodaka/steerablepyramid
공식 코드https://github.com/thecml/cloud-ksvd
공식 코드https://github.com/theoad/pscgan
공식 코드High Perceptual Quality Image Denoising with a Posterior Sampling CGAN
https://github.com/tiangexiang/BiO-Net
공식 코드BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture
https://github.com/tids-lab/its
공식 코드Boosting of Implicit Neural Representation-based Image Denoiser
https://github.com/tommoral/dicodile
공식 코드https://github.com/trile83/rqunetvae
공식 코드Riesz-Quincunx-UNet Variational Auto-Encoder for Satellite Image Denoising
https://github.com/tristan-deep/joint-diffusion
공식 코드https://github.com/trougnouf/compression
공식 코드On the Importance of Denoising when Learning to Compress Images
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