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

https://github.com/skkuse02/2019fall_41class_team8

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/skunkworksai/bakllava

Visual Instruction Tuning

https://github.com/smc-x/ms-resnetv2

Deep Residual Learning for Image Recognition

https://github.com/smerdov/DataCollectionSystem

Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset

https://github.com/smhall97/deep_dreaming_music

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/snjstudent/DRIT_pp

DRIT++: Diverse Image-to-Image Translation via Disentangled Representations

https://github.com/songquanpeng/XploreGAN

Exploring Unlabeled Faces for Novel Attribute Discovery

https://github.com/soumik12345/Pix2Pix

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/soumith/convnet-benchmarks

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/souravverma94/pre_trained_imgclassifier_dogBreeds

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/sovit-123/Deep-Learning-Image-Captioning

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/spiridonoff/Monet

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

https://github.com/sppsps/VGG-16-classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/sroutray/da-ganin

Unsupervised Domain Adaptation by Backpropagation

https://github.com/sroutray/pix2pix-isola

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/sshh12/multi_token

Visual Instruction Tuning

https://github.com/sss20young/Chuibbo-Flask-Server

StarGAN v2: Diverse Image Synthesis for Multiple Domains

https://github.com/stefanos50/CARLA2Real

Enhancing Photorealism Enhancement

https://github.com/stefkim/stylegan-batik

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/stevebong31/stargan

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

https://github.com/stqc/Simple_CycleGAN_pytorch

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

https://github.com/stu92054/Domain-adaptation-on-segmentation

FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

https://github.com/suhas1999/Flip-kart-grid-challenge

Deep Residual Learning for Image Recognition

https://github.com/sumfish/music-style-transfer

Few-Shot Unsupervised Image-to-Image Translation

https://github.com/sumitkutty/Anti-Spoof-Face-Recognition

Deep Residual Learning for Image Recognition

https://github.com/sungyoonahn/Hint-based-image-colorization-using-Attention-Unet

Deep Residual Learning for Image Recognition

https://github.com/sunjungAn/Tensorflow2.x-CV

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/sunlizhuang/YOLOv1-PaddlePaddle

Deep Residual Learning for Image Recognition

https://github.com/sunniesuhyoung/DST

WarpGAN: Automatic Caricature Generation

https://github.com/sunnysoni97/single_image_fl

Deep Residual Learning for Image Recognition

https://github.com/sunsmarterjie/chatterbox

Visual Instruction Tuning

https://github.com/susomena/DeepSlowMotion

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/svdesai/heading-date-estimation

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/svikramank/pix2pix

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/swasun/VQ-VAE-images

Deep Residual Learning for Image Recognition

https://github.com/swetak20/Deep_into_CNNs

Very Deep Convolutional Networks for Large-Scale Image Recognition

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