Papers with Code 아카이브

3D Face Modelling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

2

보존된 평가 기록

3

코드

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

https://github.com/sungyoonahn/Hint-based-image-colorization-using-Attention-Unet

Deep Residual Learning for Image Recognition

https://github.com/sunil-rival/insightface

MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition

https://github.com/sunjungAn/Tensorflow2.x-CV

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/sunlizhuang/YOLOv1-PaddlePaddle

Deep Residual Learning for Image Recognition

https://github.com/sunnysoni97/single_image_fl

Deep Residual Learning for Image Recognition

https://github.com/superaidou123/face_classification

Real-time Convolutional Neural Networks for Emotion and Gender Classification

https://github.com/suruoxi/DistanceWeightedSampling

Sampling Matters in Deep Embedding Learning

https://github.com/susan-amin/SparseBaseline1

Continuous control with deep reinforcement learning

https://github.com/susanwe/ope_worldmodels

World Models

https://github.com/susmith98/Face_Recognition

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/susomena/DeepSlowMotion

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/suvhradipghosh07/Augmented-Random-Search

Simple random search provides a competitive approach to reinforcement learning

https://github.com/suyash0612/face_recognitionandverification

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/svdesai/heading-date-estimation

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/svikramank/dm_control

DeepMind Control Suite

https://github.com/svjack/Detector-in-Detector

Detector-in-Detector: Multi-Level Analysis for Human-Parts

https://github.com/sw-gong/spiralnet_plus

4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications

https://github.com/swasun/VQ-VAE-images

Deep Residual Learning for Image Recognition

https://github.com/swayanshu/Deep-Fake-Detection

In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking

https://github.com/swetak20/Deep_into_CNNs

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/swghosh/DeepFace

https://github.com/syigzaw/WorldModels

World Models

https://github.com/syiin/ann_cancer_detection

Deep Residual Learning for Image Recognition

https://github.com/syiin/resnet_cancer_detection

Deep Residual Learning for Image Recognition

https://github.com/synthlabsai/big-math

Proximal Policy Optimization Algorithms

https://github.com/t-ae/progan-s4tf

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

https://github.com/t0930198/backup

Deep Residual Learning for Image Recognition

https://github.com/t3p/baselines

Policy Optimization via Importance Sampling

https://github.com/taekwan-lee/Virtual-Softmax-TF

Virtual Class Enhanced Discriminative Embedding Learning

https://github.com/tahasamavati/facial_expression_recognition_cnn

Real-time Convolutional Neural Networks for Emotion and Gender Classification

https://github.com/takhemlata/ssl_anti-spoofing

Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation

https://github.com/takiyu/hyperface

HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition

https://github.com/taku-y/20181125-pybullet

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/takuseno/d3rlpy

Off-Policy Deep Reinforcement Learning without Exploration

https://github.com/takuseno/ppo

Proximal Policy Optimization Algorithms

https://github.com/tallysprado/myDarknet

Focal Loss for Dense Object Detection

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