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/chiyuzhang94/pmlm-sft

공식 코드

Improving Social Meaning Detection with Pragmatic Masking and Surrogate Fine-Tuning

https://github.com/chjinny/LAN

공식 코드

LAN: Learning to Adapt Noise for Image Denoising

https://github.com/chocowu/mre-ise

공식 코드

Information Screening whilst Exploiting! Multimodal Relation Extraction with Feature Denoising and Multimodal Topic Modeling

https://github.com/chongwang1024/rdmd

공식 코드

Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual

https://github.com/chorlinglau/poetrydiffusion

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PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation

https://github.com/chqwer2/multi-view-self-supervised-disentanglement-denoising

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Multi-view Self-supervised Disentanglement for General Image Denoising

https://github.com/christopher-beckham/validation-metrics-offline-mbo

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Exploring validation metrics for offline model-based optimisation with diffusion models

https://github.com/chunminghe/awesome-diffusion-models-in-low-level-vision

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Diffusion Models in Low-Level Vision: A Survey

https://github.com/chxy95/HDRUNet

공식 코드

HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization

https://github.com/chz816/esacl

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Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization

https://github.com/ciampluca/diffusion_semi_supervised_biomedical_image_segmentation

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Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

https://github.com/cientgu/vq-diffusion

공식 코드

Vector Quantized Diffusion Model for Text-to-Image Synthesis

https://github.com/cig-skoltech/deep_demosaick

공식 코드

Iterative Joint Image Demosaicking and Denoising using a Residual Denoising Network

https://github.com/circcclek/ts-diff

공식 코드

TS-Diff: Two-Stage Diffusion Model for Low-Light RAW Image Enhancement

https://github.com/cityu-aim-group/gfbs

공식 코드

Exploring Gradient Flow Based Saliency for DNN Model Compression

https://github.com/cjbaq-origami/origami_inference

공식 코드

Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments

https://github.com/cjlee94/slice2slice

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Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction

https://github.com/cjw2021/sov-stg

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Focusing on what to decode and what to train: SOV Decoding with Specific Target Guided DeNoising and Vision Language Advisor

https://github.com/cjw2021/sov-stg-vla

공식 코드

Focusing on what to decode and what to train: SOV Decoding with Specific Target Guided DeNoising and Vision Language Advisor

https://github.com/ckiplab/hfnd

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H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation Extraction

https://github.com/ckkelvinchan/basicvsr_plusplus

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On the Generalization of BasicVSR++ to Video Deblurring and Denoising

https://github.com/ckovach/HOSD

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Decomposition of Higher-Order Spectra for Blind Multiple-Input Deconvolution, Pattern Identification and Separation

https://github.com/cl2-uwaterloo/genplan

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GenPlan: Generative Sequence Models as Adaptive Planners

https://github.com/clabat9/topological-slepians

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Topological Slepians: Maximally Localized Representations of Signals over Simplicial Complexes

https://github.com/clovaai/cutblur

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Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy

https://github.com/clwan/BIND

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Denoising individual bias for a fairer binary submatrix detection

https://github.com/cmach508/sp-gra2seq

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Linking Sketch Patches by Learning Synonymous Proximity for Graphic Sketch Representation

https://github.com/cnjianliu/diff9d

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

https://github.com/coderwzw/bod

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Efficient Bi-Level Optimization for Recommendation Denoising

https://github.com/cognaclee/dpm-ot

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DPM-OT: A New Diffusion Probabilistic Model Based on Optimal Transport

https://github.com/coleygroup/del_qsar

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Machine learning on DNA-encoded library count data using an uncertainty-aware probabilistic loss function

https://github.com/colossal-compsci/few-shot-bird-call

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An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed Pigeon

https://github.com/compression-framework/compression_framwork_for_tesing

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An End-to-End Compression Framework Based on Convolutional Neural Networks

https://github.com/computational-imaging-ru/zs-ncdenoiser

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Zero-shot denoising via neural compression: Theoretical and algorithmic framework

https://github.com/congliuUvA/Multivector-Neurons

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Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural Networks

https://github.com/conor-horgan/DeepeR

공식 코드

High-throughput molecular imaging via deep learning enabled Raman spectroscopy

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