Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

2

보존된 평가 기록

3

코드

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

https://github.com/sdauzcm/sr-basicsr

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/sdll/hrnet-pose-estimation

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/sdu2011/darknet_alexyab

Focal Loss for Dense Object Detection

https://github.com/seansoleyman/cifar10-resnet

Deep Residual Learning for Image Recognition

https://github.com/seasonSH/DocFace

DocFace: Matching ID Document Photos to Selfies

https://github.com/sebastiaopamplona/msc-thesis-deepfsim

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/sebsquire/Dogs-and-cats-image-classification-CNN

Deep Residual Learning for Image Recognition

https://github.com/sebsquire/FlowersRecognition_keras

Deep Residual Learning for Image Recognition

https://github.com/seishinkikuchi/test

Deep Residual Learning for Image Recognition

https://github.com/semi0612/cat_and_dog_vgg

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/senguptaumd/SfSNet

An All-In-One Convolutional Neural Network for Face Analysis

https://github.com/seongilp/DFE604-2020F-FinalProject

FaceForensics++: Learning to Detect Manipulated Facial Images

https://github.com/serengil/deepface

Deep Learning Face Representation by Joint Identification-Verification

https://github.com/serengil/retinaface

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/sergkuzn148/lol3

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/sergkuzn148/stg

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/serre-lab/gala_tpu

Deep Residual Learning for Image Recognition

https://github.com/setharram/facenet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/seungjaeryanlee/osim-rl-helper

Continuous control with deep reinforcement learning

https://github.com/seungju-k1m/sac-td3-td7

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/sevenHsu/Face_Recognition_IN_Video

SphereFace: Deep Hypersphere Embedding for Face Recognition

https://github.com/seyrankhademi/ResNet_CIFAR10

Deep Residual Learning for Image Recognition

https://github.com/sgoldyaev/DeepFashion.ADGAN

Controllable Person Image Synthesis with Attribute-Decomposed GAN

https://github.com/sgrvinod/a-pytorch-tutorial-to-super-resolution

Deep Residual Learning for Image Recognition

https://github.com/shahabi8/Deep-Reinforcement-Learning

Continuous control with deep reinforcement learning

https://github.com/shahbuland/basic-gans

Progressive Growing of GANs for Improved Quality, Stability, and Variation

https://github.com/shahidul56/Tiny_Faces_in_Tensorflow_msc

Can we still avoid automatic face detection?

https://github.com/shahin-01/vqa-ad

Continuous control with deep reinforcement learning

https://github.com/shakedzy/warehouse

Continuous control with deep reinforcement learning

https://github.com/shamanez/Variational-Discriminator-Bottleneck-Tensorflow-Implementation

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

https://github.com/shanxuanchen/FacialExpressionRecognition

Island Loss for Learning Discriminative Features in Facial Expression Recognition

https://github.com/shao-chi/ImageCaption

Deep Residual Learning for Image Recognition

https://github.com/shariff94/Facial_Keypoint_Detection

Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet

https://github.com/shashigharti/secure-privateai-scholarship-challenge

Focal Loss for Dense Object Detection

https://github.com/shehrum/RL_Continous-Control

Continuous control with deep reinforcement learning

https://github.com/shenwei1231/caffe-DeepRegressionForests

Deep Regression Forests for Age Estimation

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