Papers with Code 아카이브

Denoising

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하위 태스크: 6
평가표: 6
보존된 평가 기록: 15

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/kbui1993/official_aitv_poisson_denoising

공식 코드

Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising

https://github.com/kciiiman/dd_lnl

공식 코드

Dataset Distillers Are Good Label Denoisers In the Wild

https://github.com/kdmsit/TGDMat

공식 코드

Periodic Materials Generation using Text-Guided Joint Diffusion Model

https://github.com/keitakurita/robust_toxicity_detection

공식 코드

Towards Robust Toxic Content Classification

https://github.com/keiv4n/igl

공식 코드

Informed Graph Learning By Domain Knowledge Injection and Smooth Graph Signal Representation

https://github.com/kevinegan31/argos

공식 코드

Automatically identifying ordinary differential equations from data

https://github.com/kevinrojas1499/zod-mc

공식 코드

Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion

https://github.com/kevtimova/deep-sparse

공식 코드

Sparse Coding with Multi-Layer Decoders using Variance Regularization

https://github.com/kexin-kxzhang/cd2-tsi

공식 코드

Cross-Domain Conditional Diffusion Models for Time Series Imputation

https://github.com/khainb/rpsw

공식 코드

Sliced Wasserstein with Random-Path Projecting Directions

https://github.com/khaledkah/morered

공식 코드

Molecular relaxation by reverse diffusion with time step prediction

https://github.com/khb1698/drpose

공식 코드

Diffusion-based Pose Refinement and Muti-hypothesis Generation for 3D Human Pose Estimaiton

https://github.com/kherchouche-anouar/2DAE

공식 코드

Detect and Defense Against Adversarial Examples in Deep Learning using Natural Scene Statistics and Adaptive Denoising

https://github.com/khhungg/MECG-E

공식 코드

MECG-E: Mamba-based ECG Enhancer for Baseline Wander Removal

https://github.com/kidist-amde/adv-kd

공식 코드

Adv-KD: Adversarial Knowledge Distillation for Faster Diffusion Sampling

https://github.com/kilian888/discrete_dppm_graphs

공식 코드

Diffusion Models for Graphs Benefit From Discrete State Spaces

https://github.com/kimiandj/slicedwass_abc

공식 코드

Approximate Bayesian Computation with the Sliced-Wasserstein Distance

https://github.com/kirtsy/dermoscopicdataset

공식 코드

Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification

https://github.com/kk42yy/costodet-ddpm

공식 코드

CoStoDet-DDPM: Collaborative Training of Stochastic and Deterministic Models Improves Surgical Workflow Anticipation and Recognition

https://github.com/kligvasser/xUnit

공식 코드

Dense xUnit Networks

https://github.com/kmittle/ap-ldm

공식 코드

AP-LDM: Attentive and Progressive Latent Diffusion Model for Training-Free High-Resolution Image Generation

https://github.com/knodle/knodle

공식 코드

ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak Supervision

https://github.com/komyeongjin/specdiff-gan

공식 코드

Adversarial Training of Denoising Diffusion Model Using Dual Discriminators for High-Fidelity Multi-Speaker TTS

https://github.com/kong13661/act

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ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models

https://github.com/kongdai123/consistency2

공식 코드

Consistency^2: Consistent and Fast 3D Painting with Latent Consistency Models

https://github.com/kongds/prompt-bert

공식 코드

PromptBERT: Improving BERT Sentence Embeddings with Prompts

https://github.com/kongzhecn/cfd-pad

공식 코드

Fingerprint Presentation Attack Detection by Channel-wise Feature Denoising

https://github.com/kongzhecn/omg

공식 코드

OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models

https://github.com/koninik/wordstylist

공식 코드

WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models

https://github.com/kornia/kornia

공식 코드

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

https://github.com/kpeng9510/hyprometa

공식 코드

Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization

https://github.com/krennic999/mpi

공식 코드

Masked Pre-training Enables Universal Zero-shot Denoiser

https://github.com/krishnaswamylab/heatgeo

공식 코드

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction

https://github.com/kritiksoman/GIMP-ML

공식 코드

GIMP-ML: Python Plugins for using Computer Vision Models in GIMP

https://github.com/krulllab/DVLAE

공식 코드

Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise

https://github.com/krulllab/cosdd

공식 코드

Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.