Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

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평가표

2

보존된 평가 기록

3

코드

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

https://github.com/yashclone999/ResNet_MODEL

Deep Residual Learning for Image Recognition

https://github.com/yashraj02/RetinaFace

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/yaxingwang/MineGAN

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

https://github.com/ycao5602/SAL

Deep Residual Learning for Image Recognition

https://github.com/ycxioooong/MovieSynopsisAssociation

Unifying Identification and Context Learning for Person Recognition

https://github.com/yczhang1017/SSD_resnet_pytorch

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/yehengchen/FaceNet-FaceRecognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/yehengchen/FaceRecognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/yehengchen/FaceRecognition-FaceNet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/yehengchen/SmartCar-FaceRecognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/yellowfighter2333/ticket-machine-with-face-recognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/yellowfighter2333/ticket-mechine-with-face-recognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/yerfor/geneface

GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face Synthesis

https://github.com/yevgm/deepadv3d

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

https://github.com/yfeng95/deca

VGGFace2: A dataset for recognising faces across pose and age

https://github.com/yfsin/deepfake_pro

DeepFaceLab: Integrated, flexible and extensible face-swapping framework

https://github.com/yh-iro/Keras-TP-GAN

Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

https://github.com/yhenon/pytorch-retinanet

Focal Loss for Dense Object Detection

https://github.com/yhisaki/average-reward-drl

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

https://github.com/yibeiou/Advanced_Business_Intelligence

Deep Residual Learning for Image Recognition

https://github.com/yifan12wu/td3-jax

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/yifeizhou02/bt-2

Towards Backward-Compatible Representation Learning

https://github.com/yihaosun1124/OfflineRL-Kit

MOPO: Model-based Offline Policy Optimization

https://github.com/yijiaceline/Final-Project-Group4

Focal Loss for Dense Object Detection

https://github.com/yijiazh/DFER_Summer2019

Deep Facial Expression Recognition: A Survey

https://github.com/yimingpeng/sac-master

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

https://github.com/yining043/SAC-discrete

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

https://github.com/yiningzeng/darknet-fork-from-AlexeyAB

Focal Loss for Dense Object Detection

https://github.com/yiyuan1991/3D-Face-GCNs

Towards High-Fidelity 3D Face Reconstruction from In-the-Wild Images Using Graph Convolutional Networks

https://github.com/yjzhai-cs/vehicle-10

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/yoavalon/Quadcopter-env

Proximal Policy Optimization Algorithms

https://github.com/yoavalon/QuadcopterReinforcementLearning

Proximal Policy Optimization Algorithms

https://github.com/yoboget/CProGAN-ME

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

https://github.com/yoshitomo-matsubara/torchdistill

Deep Residual Learning for Image Recognition

https://github.com/young-geng/cql

Conservative Q-Learning for Offline Reinforcement Learning

https://github.com/young-geng/jaxcql

Conservative Q-Learning for Offline Reinforcement Learning

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