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/cambridge-mlg/neural_diffusion_processes

공식 코드

Geometric Neural Diffusion Processes

https://github.com/cammarasana123/weightedconvolution

공식 코드

Optimal Density Functions for Weighted Convolution in Learning Models

https://github.com/cammarasana123/weightedconvolution2.0

공식 코드

Optimal Weighted Convolution for Classification and Denosing

https://github.com/cao-cong/RViDeNet

공식 코드

Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes

https://github.com/cardiacvision/diffusion

공식 코드

Dreaming of Electrical Waves: Generative Modeling of Cardiac Excitation Waves using Diffusion Models

https://github.com/cardio-ai/mfvi-dip-mia

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Posterior temperature optimized Bayesian models for inverse problems in medical imaging

https://github.com/castorini/daam

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What the DAAM: Interpreting Stable Diffusion Using Cross Attention

https://github.com/castorini/touche-error-analysis

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Systematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR

https://github.com/casus/pi-ddpm

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Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model

https://github.com/cchen-cc/sfda-dpl

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Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling

https://github.com/cd-athena/movidnn

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MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural Networks

https://github.com/cdb342/alocc

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ALOcc: Adaptive Lifting-based 3D Semantic Occupancy and Cost Volume-based Flow Prediction

https://github.com/cg563/low-frequency-adversarial

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Low Frequency Adversarial Perturbation

https://github.com/cgcl-codes/eclipse

공식 코드

ECLIPSE: Expunging Clean-label Indiscriminate Poisons via Sparse Diffusion Purification

https://github.com/changlee0903/d4am

공식 코드

D4AM: A General Denoising Framework for Downstream Acoustic Models

https://github.com/changsn/FlexDiT

공식 코드

FlexDiT: Dynamic Token Density Control for Diffusion Transformer

https://github.com/changwxx/csot-for-lnl

공식 코드

CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels

https://github.com/changyaotian/addp

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ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process

https://github.com/chao1224/geossl

공식 코드

Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching

https://github.com/chao1224/se3ddm

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Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching

https://github.com/chaoshangcs/VIGAN

공식 코드

VIGAN: Missing View Imputation with Generative Adversarial Networks

https://github.com/chaowentao/lfsrdiff

공식 코드

LFSRDiff: Light Field Image Super-Resolution via Diffusion Models

https://github.com/chaowentao/maskblur

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MaskBlur: Spatial and Angular Data Augmentation for Light Field Image Super-Resolution

https://github.com/charlesglucas/sugar_dms

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Hyperparameter selection for Discrete Mumford-Shah

https://github.com/charlesmillard/Noisier2Noise_for_recon

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A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noise

https://github.com/charlesmillard/robust_ssdu

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Clean self-supervised MRI reconstruction from noisy, sub-sampled training data with Robust SSDU

https://github.com/charliezcj/utvnet

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Adaptive Unfolding Total Variation Network for Low-Light Image Enhancement

https://github.com/chenchao15/localn2nm

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Inferring Neural Signed Distance Functions by Overfitting on Single Noisy Point Clouds through Finetuning Data-Driven based Priors

https://github.com/chengyiliu-cs/generative-diffusion-models-on-graphs

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Generative Diffusion Models on Graphs: Methods and Applications

https://github.com/chengzhag/panfusion

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Taming Stable Diffusion for Text to 360° Panorama Image Generation

https://github.com/chenhaoxing/DiffusionInst

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DiffusionInst: Diffusion Model for Instance Segmentation

https://github.com/chenning0115/spectraldiff

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SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Models

https://github.com/chenyangqiqi/bsvd

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Real-time Streaming Video Denoising with Bidirectional Buffers

https://github.com/chenz418/viis

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VIIS: Visible and Infrared Information Synthesis for Severe Low-light Image Enhancement

https://github.com/chinmay5/vessel_diffuse

공식 코드

3D Vessel Graph Generation Using Denoising Diffusion

https://github.com/chinsengi/score_rnn

공식 코드

Expressive probabilistic sampling in recurrent neural networks

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