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

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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/nav74neet/ddpg_biped

Continuous control with deep reinforcement learning

https://github.com/nav74neet/rl4biped

Continuous control with deep reinforcement learning

https://github.com/naver-ai/StyleMapGAN

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

https://github.com/naykun/tf_pg_gans

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

https://github.com/ndb796/pytorch-adversarial-training-cifar

Deep Residual Learning for Image Recognition

https://github.com/nddoshi/pointnet

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

https://github.com/near32/regym

Proximal Policy Optimization Algorithms

https://github.com/neelabh17/MAVI-Face

RetinaFace: Single-stage Dense Face Localisation in the Wild

https://github.com/neerajvashistha/vgg16

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/negarhdr/skeleton-based-action-recognition

Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation

https://github.com/neilsgp/RL-Algorithms

Sample Efficient Actor-Critic with Experience Replay

https://github.com/nelson-mig-l/boofcv-dithering

Image-based Portrait Engraving

https://github.com/neshitov/UNet

Focal Loss for Dense Object Detection

https://github.com/neuralet/facemask

Finding Tiny Faces

https://github.com/neuroevolution-ai/ProcgenAutoencoder

World Models

https://github.com/neverUseThisName/Decorrelated-Adversarial-Learning

Decorrelated Adversarial Learning for Age-Invariant Face Recognition

https://github.com/neverUseThisName/Face-X-Ray

Face X-ray for More General Face Forgery Detection

https://github.com/ngonthier/multiresolution_texture

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/nguoido/Yolo-alexeyAB

Focal Loss for Dense Object Detection

https://github.com/nhanvu39/ArcFace

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/nhatduy19599/insightface-master

ArcFace: Additive Angular Margin Loss for Deep Face Recognition

https://github.com/nhynes/abc

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning

https://github.com/nicaogr/multiresolution_texture

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/nicklashansen/tdmpc2

DeepMind Control Suite

https://github.com/nicku-a/Weather_Classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/nicolalandro/Padam

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/nidolow/image-classification

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/nii-yamagishilab/ClassNSeg

Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos

https://github.com/nikhilbarhate99/PPO

Proximal Policy Optimization Algorithms

https://github.com/nikhilbarhate99/PPO-PyTorch

Proximal Policy Optimization Algorithms

https://github.com/nikhilbarhate99/TD3-PyTorch-BipedalWalker-v2

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/nikitakaraevv/pointnet

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

https://github.com/nikolaevs92/DL-articles-implementation

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/nilseuropa/pfdl_ncnn

PFLD: A Practical Facial Landmark Detector

https://github.com/nilseuropa/pfld_ncnn

PFLD: A Practical Facial Landmark Detector

https://github.com/nilseuropa/ros_img2pose

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation

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