Papers with Code 아카이브
Denoising
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 6
- 보존된 평가 기록
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Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.
<span style="color:grey; opacity: 0.6">( Image credit: Beyond a Gaussian Denoiser )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/cooelf/instancereg
공식 코드Instance Regularization for Discriminative Language Model Pre-training
https://github.com/cp3wan/dformer
공식 코드DFormer: Diffusion-guided Transformer for Universal Image Segmentation
https://github.com/cpu9xx/ael
공식 코드When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation
https://github.com/crosszamirski/guided-i2i
공식 코드Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels
https://github.com/csdwren/sfarl
공식 코드Simultaneous Fidelity and Regularization Learning for Image Restoration
https://github.com/csguoh/adaptir
공식 코드Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts
https://github.com/csjianyang/ganlm
공식 코드GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator
https://github.com/csjunxu/Noisy-As-Clean
공식 코드Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image
https://github.com/csjunxu/PolyUDataset
공식 코드https://github.com/csm9493/FBI-Denoiser
공식 코드FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise
https://github.com/csm9493/FC-AIDE-Keras
공식 코드https://github.com/csm9493/GAN2GAN
공식 코드GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images
https://github.com/cswin/RC-Nets
공식 코드Image Restoration Using Deep Regulated Convolutional Networks
https://github.com/cswin/WIN
공식 코드Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior
https://github.com/csyanbin/3d-medical-generative-survey
공식 코드https://github.com/cszhilu1998/bracketire
공식 코드Exposure Bracketing Is All You Need For A High-Quality Image
https://github.com/cszhilu1998/selfir
공식 코드Self-Supervised Image Restoration with Blurry and Noisy Pairs
https://github.com/cszn/DnCNN
공식 코드Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/cszn/FFDNet
공식 코드FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
https://github.com/cszn/ircnn
공식 코드https://github.com/cszn/scunet
공식 코드Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis
https://github.com/cubeyoung/Noise2Score
공식 코드Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Images
https://github.com/cuhk-aim-group/diffrect
공식 코드DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation
https://github.com/cumulo-autumn/streamdiffusion
공식 코드StreamDiffusion: A Pipeline-level Solution for Real-time Interactive Generation
https://github.com/cvc-lab/patch-subspace-learning-autoencoder
공식 코드Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal Processing
https://github.com/cvignac/digress
공식 코드https://github.com/cvignac/midi
공식 코드MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
https://github.com/cwc1260/handdagt
공식 코드HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose Estimation
https://github.com/cy623/r2lp
공식 코드Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
https://github.com/cylumn/daare
공식 코드Removing Radio Frequency Interference from Auroral Kilometric Radiation with Stacked Autoencoders
https://github.com/cynicarlos/retinexrawmamba
공식 코드Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
https://github.com/cyrilsterling/textgen
공식 코드How Control Information Influences Multilingual Text Image Generation and Editing?
https://github.com/cyrus2d/cyrus2dbase
공식 코드Observation Denoising in CYRUS Soccer Simulation 2D Team For RoboCup 2023
https://github.com/cyrus2d/cyrusloganalyzer
공식 코드Observation Denoising in CYRUS Soccer Simulation 2D Team For RoboCup 2024
https://github.com/cywinski/saeuron
공식 코드SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders
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