Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

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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/raghakot/keras-resnet

Deep Residual Learning for Image Recognition

https://github.com/raguilar-f/Thermal-Face-Recognition-Using-Convolutional-Neural-Networks-and-Transfer-Learning

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/raguilar-f/Thermal-face-recognition-using-transfer-learning

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/rahowa/catboost_focal_loss

Focal Loss for Dense Object Detection

https://github.com/rahul-t-p/ASVspoof-2019

Deep Residual Learning for Image Recognition

https://github.com/rahulchaurasiya1/cautious-waddle

Deep Residual Learning for Image Recognition

https://github.com/rahuls02/Image-Noise-Reduction

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

https://github.com/rainofmine/Face_Attention_Network

Focal Loss for Dense Object Detection

https://github.com/raj-gupta1/Flower-Species-Classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/raj-gupta1/Tomato-leaves-disease-Predictor

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/raja17021998/Augmented-Random-Search-Implementation

Simple random search provides a competitive approach to reinforcement learning

https://github.com/rajatsahay/Pose2Pose

Everybody Dance Now

https://github.com/rajneeshaggarwal/google-efficientnet

Deep Residual Learning for Image Recognition

https://github.com/ram-ch/RealTimeFaceRecognition

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

https://github.com/ramanans1/dm_control

DeepMind Control Suite

https://github.com/ran-weii/cleanil

When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning

https://github.com/random-quark/progressive-gan-completion

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

https://github.com/rap-music/-

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/raspstephan/sugar-flower-fish-or-gravel

Focal Loss for Dense Object Detection

https://github.com/raulsteleac/Speech_Emotion_Recognition

Transfer Learning for Improving Speech Emotion Classification Accuracy

https://github.com/raunak222/Facial-Keypint-Detection

Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet

https://github.com/raunak222/Facial-Keypoint-Detection

Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet

https://github.com/ravi-lanka-4/CoPiEr

Co-training for Policy Learning

https://github.com/ray-project/ray/tree/master/rllib

Continuous control with deep reinforcement learning

https://github.com/rcheng805/RL-CBF

End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

https://github.com/rddy/ReQueST

Learning Human Objectives by Evaluating Hypothetical Behavior

https://github.com/rdgozum/dexpression-pytorch

DeXpression: Deep Convolutional Neural Network for Expression Recognition

https://github.com/realmichaelye/Skin-Lesions-Classifier-ResNet50

Deep Residual Learning for Image Recognition

https://github.com/rebeccagio/object_detection

Focal Loss for Dense Object Detection

https://github.com/redcaps-dataset/pytorch-retinaface

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/rehamessameltagoury/Urban-Self-Driving-Car

End-to-end Multi-Modal Multi-Task Vehicle Control for Self-Driving Cars with Visual Perception

https://github.com/rehoss/lbmpc_semimarkov

An Experimental Design Perspective on Model-Based Reinforcement Learning

https://github.com/reinforcement-learning-kr/lets-do-irl

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

https://github.com/reinforcement-learning-kr/pg_travel

Proximal Policy Optimization Algorithms

https://github.com/reiniscimurs/TD3_Separate_Action

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/rejuvyesh/rllab

Benchmarking Deep Reinforcement Learning for Continuous Control

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