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/luke-bhan/TwitterSentimentAnalysisTool

Continuous control with deep reinforcement learning

https://github.com/lukebhan/TwitterSentimentAnalysisTool

Continuous control with deep reinforcement learning

https://github.com/lxy000719/ResNet-50-pneumonia-classification

Deep Residual Learning for Image Recognition

https://github.com/lyatdawn/lightcnn-mxnet

A Light CNN for Deep Face Representation with Noisy Labels

https://github.com/lyk19940625/MyRFBNet

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/lyp-deeplearning/awesome-retinal-registration

MOS: A Low Latency and Lightweight Framework for Face Detection, Landmark Localization, and Head Pose Estimation

https://github.com/lyp741/Pytorch-ERL

Evolution-Guided Policy Gradient in Reinforcement Learning

https://github.com/lzx551402/ASLFeat

Circle Loss: A Unified Perspective of Pair Similarity Optimization

https://github.com/m-117/PointNet-ein-Implementationsbeispiel-mit-Jupyter-Notebooks

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

https://github.com/m-kahla/Label-Only-Model-Inversion-Attacks-via-Boundary-Repulsion

Label-Only Model Inversion Attacks via Boundary Repulsion

https://github.com/m5823779/DDPG

Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation

https://github.com/m5823779/MotionPlannerUsingDDPG

Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation

https://github.com/ma921/XRDidentifier

AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations

https://github.com/ma9o/facematch

Deep Face Recognition: A Survey

https://github.com/mabhay3420/Deep-Into-CNN

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/machanic/AU_R-CNN

AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection

https://github.com/maciejdomagala/DLWP_notes

Deep Residual Learning for Image Recognition

https://github.com/mackitron/COVID19

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/madhavambati/Face-Recognition

Network In Network

https://github.com/madhur-tandon/RL-Project

Continuous control with deep reinforcement learning

https://github.com/madvn/DDPG

Continuous control with deep reinforcement learning

https://github.com/maggie0106/Graph-CNN-in-3D-Point-Cloud-Classification

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

https://github.com/magicsunday/pico

Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

https://github.com/magnificent1208/r3det-on-mmdetection

Deep Residual Learning for Image Recognition

https://github.com/magnusja/ppo

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/mahathi26/ciss

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/mahmoodlab/hest

Deep Residual Learning for Image Recognition

https://github.com/mahxn0/RetinaFace_For_Face_Plate_Detect

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/majercakdavid/gym-virtual-quant-trading

Continuous control with deep reinforcement learning

https://github.com/makatx/YOLO_ResNet

Deep Residual Learning for Image Recognition

https://github.com/malin9402/2020-0221

Deep Residual Learning for Image Recognition

https://github.com/malin9402/arcface

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/malin9402/retiface

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/manankshastri/ART

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/manishravula/yolov3_tiny_pruned

Focal Loss for Dense Object Detection

https://github.com/manoranjan03/PaperImplementations

Deep Residual Learning for Image Recognition

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