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3D Architecture

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ZezhouCheng/GP-DIP

A Bayesian Perspective on the Deep Image Prior

https://github.com/ZhengJun-AI/MoirePhotoRestoration-MCNN

Moiré Photo Restoration Using Multiresolution Convolutional Neural Networks

https://github.com/Zhengqi-Wu/Unrolled-optimization-with-deep-priors

Unrolled Optimization with Deep Priors

https://github.com/ZhenyuTan/Noise2Noise-Cryo-EM-image-denoising

Noise2Noise: Learning Image Restoration without Clean Data

https://github.com/aaronmckinstry706/toward-robust-dnn

Towards Deep Neural Network Architectures Robust to Adversarial Examples

https://github.com/abbasi-ali/noise2self

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

https://github.com/acasamitjana/jump

Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining

https://github.com/acids-ircam/diffusion_models

Denoising Diffusion Probabilistic Models

https://github.com/adam-mah/Medical-Image-Denoising

Medical image denoising using convolutional denoising autoencoders

https://github.com/adam-mehdi/MuarAugment

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

https://github.com/adverML/GuidedDiffusionPur

Guided Diffusion Model for Adversarial Purification

https://github.com/ah7149407/ee193-03_project

DeepISP: Towards Learning an End-to-End Image Processing Pipeline

https://github.com/ai-med/stablepose

HumanSD: A Native Skeleton-Guided Diffusion Model for Human Image Generation

https://github.com/aiff22/PyNET-PyTorch

Replacing Mobile Camera ISP with a Single Deep Learning Model

https://github.com/aimagelab/multimodal-garment-designer

Multimodal-Conditioned Latent Diffusion Models for Fashion Image Editing

https://github.com/ajazturki10/Credit-Card-Fraud-Detection-using-Autoencoders

Credit Card Fraud Detection Using Autoencoder Neural Network

https://github.com/akalia77/hinet

HINet: Half Instance Normalization Network for Image Restoration

https://github.com/akashsonowal/ddpo-pytorch

Training Diffusion Models with Reinforcement Learning

https://github.com/akshaymehra24/poisoning_certified_defenses

Penalty Method for Inversion-Free Deep Bilevel Optimization

https://github.com/alanqrwang/RegAgnosticCSMRI

Computing Multiple Image Reconstructions with a Single Hypernetwork

https://github.com/albarji/toy-diffusion

Denoising Diffusion Probabilistic Models

https://github.com/albrateanu/LYT-Net/tree/main/PyTorch

LYT-NET: Lightweight YUV Transformer-based Network for Low-light Image Enhancement

https://github.com/aleks-krasowski/pinnfluence_resampling

Input Similarity from the Neural Network Perspective

https://github.com/alexander-prutko/mil-audio-denoising

Speech Denoising with Deep Feature Losses

https://github.com/alexzhou907/pvd

3D Shape Generation and Completion through Point-Voxel Diffusion

https://github.com/ali-vilab/VGen

ModelScope Text-to-Video Technical Report

https://github.com/ali-vilab/i2vgen-xl

ModelScope Text-to-Video Technical Report

https://github.com/alibaba/graph-gpt

dKV-Cache: The Cache for Diffusion Language Models

https://github.com/alipay/diffusion-model-for-instance-segmentation

DiffusionInst: Diffusion Model for Instance Segmentation

https://github.com/allenai/scientific-claim-generation

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/amazon-science/alexa-teacher-models

AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model

https://github.com/ambareeshsrja16/Python-Module-for-Missing-Data-Imputation

MIDA: Multiple Imputation using Denoising Autoencoders

https://github.com/anas-zafar/SSAMAN

https://github.com/anassbellache/TomoGAN

TomoGAN: Low-Dose Synchrotron X-Ray Tomography with Generative Adversarial Networks

https://github.com/anchen1011/toflow

Video Enhancement with Task-Oriented Flow

https://github.com/andreamazzitelli/ProjectNN

Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

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