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/sherkhan15/distarctor-Detection_Eyes_Emotions_CI

Real-time Convolutional Neural Networks for Emotion and Gender Classification

https://github.com/shi510/ffem

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/shijianjian/HRNet_Keras

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/shijianjian/efficientnet-pytorch-3d

Deep Residual Learning for Image Recognition

https://github.com/shijx12/AR-Tree

A Structured Self-attentive Sentence Embedding

https://github.com/shinian123/gym

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/shiningsunnyday/mcts-chess

Proximal Policy Optimization Algorithms

https://github.com/shinyingl/CV_Facial_Keypoints

Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet

https://github.com/shiqiyu/libfacedetection.train

Detect Faces Efficiently: A Survey and Evaluations

https://github.com/shoaibahmed/CrossLayerPooling

Deep Residual Learning for Image Recognition

https://github.com/shoji9x9/CIFAR-10-By-small-ResNet

Deep Residual Learning for Image Recognition

https://github.com/shoji9x9/Fashion-MNIST-By-ResNet

Deep Residual Learning for Image Recognition

https://github.com/shoutOutYangJie/Few-Shot-Adversarial-Learning-for-face-swap

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

https://github.com/shreyasc-13/off_domain_rlkit

Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers

https://github.com/shreyesss/PPO-implementation-keras-tensorflow

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/shridharrhegde/vgg-age

Deep Convolutional Neural Network for Age Estimation based on VGG-Face Model

https://github.com/shriram2112/Reinforcement_learning_gym

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/shtnkgm/VisionFrameworkSample

Deep Residual Learning for Image Recognition

https://github.com/shuShelby/main

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/shuishida/soaprl

Proximal Policy Optimization Algorithms

https://github.com/shuliyao/GANimation_TL

GANimation: Anatomically-aware Facial Animation from a Single Image

https://github.com/shuuchen/HRNet

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/shyamsn97/hyper-nn

Goal-Conditioned Generators of Deep Policies

https://github.com/shyhyawJou/ArcFace-Pytorch

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/sibozhang/Text2Video

Text-based Editing of Talking-head Video

https://github.com/sicxu/Deep3DFaceRecon_pytorch

Improving Face Anti-Spoofing by 3D Virtual Synthesis

https://github.com/siddharthbhonge/Neural_Style_transfer

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/siddharthverma314/proximalpolicyoptimization

Proximal Policy Optimization Algorithms

https://github.com/sidify/resnet_focal_loss

Deep Residual Learning for Image Recognition

https://github.com/sidward14/gan-lab

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

https://github.com/sijinkim/pggan-clone

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

https://github.com/silvialuu/DRL-2018

Proximal Policy Optimization Algorithms

https://github.com/simo-bat/Crack_detection

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/simon20010923/DDAMFN

https://github.com/simonjisu/nsmc_study

A Structured Self-attentive Sentence Embedding

https://github.com/simonlevine/11785-project

Focal Loss for Dense Object Detection

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