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/khansel01/nes-npg

Towards Generalization and Simplicity in Continuous Control

https://github.com/khawajatalhahaseeb/Class-Activation-Map-Keras

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/khrlimam/facenet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/khurram702/StyleBasedGAN

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/khyeyoon/face_recognition

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/kim1102/PPL-MFR

https://github.com/kiminh/dual-policy-distillation

Dual Policy Distillation

https://github.com/kingcong/HRNetW48_seg

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/kingcong/Zero-DCE

Low-Light Image and Video Enhancement Using Deep Learning: A Survey

https://github.com/kingcong/Zero-DCE-

Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation

https://github.com/kingcong/gpu_ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/kingcong/gpu_FaceAttribute

Deep Residual Learning for Image Recognition

https://github.com/kingcong/gpu_HRNetW48_cls

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/kingcong/gpu_SE-Net

Deep Residual Learning for Image Recognition

https://github.com/kingcong/resnet

Deep Residual Learning for Image Recognition

https://github.com/kingsj0405/pulse-any-image

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/kiranu1024/deep-learning

Deep Residual Learning for Image Recognition

https://github.com/kishanAk21/Skin-Cancer-Image-Classification

Deep Residual Learning for Image Recognition

https://github.com/kishansharma3012/Deep_Head_Pose_Estimation

Fine-Grained Head Pose Estimation Without Keypoints

https://github.com/kishorkuttan/traffic_net

Deep Residual Learning for Image Recognition

https://github.com/kitliu5/Stanford-CS236-Project

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

https://github.com/kkelchte/task_free_continual_learning

Task-Free Continual Learning

https://github.com/km1414/CNN-models

Deep Residual Learning for Image Recognition

https://github.com/kmohanku/Low-Light-Image-Video-Enhancement

Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

https://github.com/kmzzhang/nbi

Deep Residual Learning for Image Recognition

https://github.com/kongzhiyou/darknet-master

Focal Loss for Dense Object Detection

https://github.com/konny0311/vgg

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/konstantinos-p/image_classification_SOTA

Deep Residual Learning for Image Recognition

https://github.com/kooBH/facenet_verification

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/kornia/kornia

Focal Loss for Dense Object Detection

https://github.com/koshian2/ResNet-MultipleFramework

Deep Residual Learning for Image Recognition

https://github.com/koshian2/swd-pytorch

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

https://github.com/krantirk/Face-detection-and-counting-

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/krantirk/Self-Supervised-photo

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/krasing/DRLearningCollaboration

Continuous control with deep reinforcement learning

https://github.com/krasing/DRLearningContinuousControl

Continuous control with deep reinforcement learning

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