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보존된 평가 기록

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코드

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

https://github.com/csjcai/DBCPeNet

https://github.com/cswry/osediff

Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-Resolution

https://github.com/cuiaiyu/street-tryon-benchmark

Learning Garment DensePose for Robust Warping in Virtual Try-On

https://github.com/cure-lab/pnpinversion

Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code

https://github.com/cvfx-2019/homework1-color-transfer

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/cvg/Hierarchical-Localization

SuperGlue: Learning Feature Matching with Graph Neural Networks

https://github.com/cviaai/PSF-GAN-ESTIMATION

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/cvlab-epfl/wide-depth-range-pose

Wide-Depth-Range 6D Object Pose Estimation in Space

https://github.com/cvp19g2/cvp19g2

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/cwbabel/faster-cnn

Mask R-CNN

https://github.com/cxt98/Densefusion-transparency

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

https://github.com/cydessole/AnimeLife

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/cyhuang-tw/AdaIN-VC

One-shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization

https://github.com/cyhuang-tw/robust-vc

Toward Degradation-Robust Voice Conversion

https://github.com/cynicaldevil/neural-style-transfer

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

https://github.com/cysmith/neural-style-tf

A Neural Algorithm of Artistic Style

https://github.com/d-dawg78/MVA_ASAIT

ACVAE-VC: Non-parallel many-to-many voice conversion with auxiliary classifier variational autoencoder

https://github.com/d-shivam/Pose-estimation-based-action-recognition-for-help-Situation-Identification

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/daewon88/Korean-Voice-Conversion

Parallel-Data-Free Voice Conversion Using Cycle-Consistent Adversarial Networks

https://github.com/dahliau/DPDist

PCRNet: Point Cloud Registration Network using PointNet Encoding

https://github.com/daintlab/ct-denoising

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/dajes/DensePose-TorchScript

DensePose: Dense Human Pose Estimation In The Wild

https://github.com/dalexanderch/CFD

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/damo-vilab/videocomposer

Composer: Creative and Controllable Image Synthesis with Composable Conditions

https://github.com/danielajisafe/Image-Captioning-Model

Show and Tell: A Neural Image Caption Generator

https://github.com/danielperezr88/multiposenet-aries

MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network

https://github.com/daniilrobnikov/vits2

YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

https://github.com/danny1984/hourglass_keras

Stacked Hourglass Networks for Human Pose Estimation

https://github.com/dantecomedia/CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/dariaip/musegan_pytorch

MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment

https://github.com/darkAlert/vibe-rt

VIBE: Video Inference for Human Body Pose and Shape Estimation

https://github.com/daspartho/magicmix

MagicMix: Semantic Mixing with Diffusion Models

https://github.com/davidgolub/charizard

Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer

https://github.com/davidstap/AttnGAN

StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

https://github.com/dawnlh/awesome-low-light-image-enhancement

Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement

https://github.com/dc3ea9f/RegionViT

RegionViT: Regional-to-Local Attention for Vision Transformers

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