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

2

보존된 평가 기록

3

코드

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

https://github.com/felipeyanez/nmf

Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence

https://github.com/felixgwu/img_classification_pk_pytorch

Deep Residual Learning for Image Recognition

https://github.com/fenghansen/ESRGAN-Keras

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/fenglian425/Agriculture_AI

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/fengredrum/cnn-xla

Deep Residual Learning for Image Recognition

https://github.com/feruxhi/thoughts

Continuous control with deep reinforcement learning

https://github.com/feryal/craft-env

Modular Multitask Reinforcement Learning with Policy Sketches

https://github.com/ffletcherr/face-recognition-liveness

Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection

https://github.com/ffr4nz/UnknownUnknowns

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/fgitmichael/SVAEfromSLAC

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

https://github.com/fgitmichael/TestModeDisentangling

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

https://github.com/fhbzc/FishAgentSimulation

Continuous control with deep reinforcement learning

https://github.com/fiberleif/nc_ddpg

Continuous control with deep reinforcement learning

https://github.com/final-0/Real-ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/final-0/Real-ESRGAN-bicubic

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/fizyr/keras-retinanet

Focal Loss for Dense Object Detection

https://github.com/flavioschneider/ml_papers_presentations

Continuous control with deep reinforcement learning

https://github.com/floodsung/DDPG

Continuous control with deep reinforcement learning

https://github.com/flora-zyx/SJNet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/flowersteam/curious

Continuous control with deep reinforcement learning

https://github.com/flowersteam/geppg

Parameter Space Noise for Exploration

https://github.com/flowersteam/rl_stats

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

https://github.com/flynn-chen/faceforensics_benchmark

FaceForensics++: Learning to Detect Manipulated Facial Images

https://github.com/flytocc/PaddleClas

PP-ShiTu: A Practical Lightweight Image Recognition System

https://github.com/fnyanez/nmf

Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence

https://github.com/foamliu/Gaze-Estimation

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/foamliu/InsightFace-PyTorch

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/foamliu/InsightFace-v2

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/foamliu/InsightFace-v3

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/foamliu/MobileFaceNet

MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices

https://github.com/foivospar/Arc2Face

Arc2Face: A Foundation Model for ID-Consistent Human Faces

https://github.com/fomorians-oss/awr

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

https://github.com/fomorians/forward-models

Recurrent Environment Simulators

https://github.com/foxer9developer/Face-Emotion-to-Emoji-Convertor

Real-time Convolutional Neural Networks for Emotion and Gender Classification

https://github.com/fpleoni/its_all_in_the_family

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/francislata/Sign-Language-Digits-CNN

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.