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

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보존된 평가 기록

3

코드

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

https://github.com/Pulkitdzrt/ML-Image-Super-Resolution

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/Punakshi/Deep-Residual-Learning-for-Image-Recognition-Implementation

Deep Residual Learning for Image Recognition

https://github.com/PushpakBhoge/Face_Recognition_TF

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/Puzer/stylegan-encoder

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/Qengineering/Face-Mask-Detection-Jetson-Nano

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/Qengineering/Face-Mask-Detection-Raspberry-Pi-64-bits

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/Qengineering/Face-detection-Raspberry-Pi-32-64-bits

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/Qengineering/LFFD-MNN-Jetson-Nano

LFFD: A Light and Fast Face Detector for Edge Devices

https://github.com/Qengineering/LFFD-MNN-Raspberry-Pi-4

LFFD: A Light and Fast Face Detector for Edge Devices

https://github.com/Qengineering/LFFD-ncnn-Jetson-Nano

LFFD: A Light and Fast Face Detector for Edge Devices

https://github.com/Qengineering/LFFD-ncnn-Raspberry-Pi-4

LFFD: A Light and Fast Face Detector for Edge Devices

https://github.com/QianliM/CAPE

Generating 3D faces using Convolutional Mesh Autoencoders

https://github.com/QuentinVacher-rl/SoftActorCritic-in-Cpp-using-LibTorch

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

https://github.com/QuocThangNguyen/deep-metric-learning-tsinghua-dogs

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/RAGHAV2998/Everybody-Can-Dance-Now-Video-game-version-

Everybody Dance Now

https://github.com/RLAgent/state-marginal-matching

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

https://github.com/Rafael1s/Deep-Reinforcement-Learning-Udacity

Proximal Policy Optimization Algorithms

https://github.com/RainbowRui/Landmark-Driven-Facial-Expression-Recognition

Suppressing Uncertainties for Large-Scale Facial Expression Recognition

https://github.com/Raj-08/Deepfake-Detection-Mesonet

MesoNet: a Compact Facial Video Forgery Detection Network

https://github.com/Rakshit-Shetty/Resnet-Implementation

Deep Residual Learning for Image Recognition

https://github.com/Ram81/AC-VAEGAN-PyTorch

CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training

https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection

Large Scale Correlation Clustering Optimization

https://github.com/Recognito-Vision/Face-SDK-Android-Demo

Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings

https://github.com/Recognito-Vision/Face-SDK-Linux-Demos

Wild Face Anti-Spoofing Challenge 2023: Benchmark and Results

https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection

DeepID3: Face Recognition with Very Deep Neural Networks

https://github.com/Remtasya/DDPG-Actor-Critic-Reinforcement-Learning-Reacher-Environment

Continuous control with deep reinforcement learning

https://github.com/RezisEwig/esrgan

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/RiS3-Lab/ModelXRay

Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps

https://github.com/RicardooYoung/LatentDistributionAdjusting

Latent Distribution Adjusting for Face Anti-Spoofing

https://github.com/RichardMathewsII/YOLBO

Focal Loss for Dense Object Detection

https://github.com/RoblabWh/RobLearn

Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments

https://github.com/RobotEdh/facenet

FaceNet: A Unified Embedding for Face Recognition and Clustering

https://github.com/RobotMobile/cv-deep-learning-paper-review

Deep Residual Learning for Image Recognition

https://github.com/RobvanGastel/svg-priors

Learning Continuous Control Policies by Stochastic Value Gradients

https://github.com/RocketFlash/easy_metric_learning/tree/master/tools

SphereFace: Deep Hypersphere Embedding for Face Recognition

https://github.com/Rohed/ml-1

Deep Residual Learning for Image Recognition

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