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/wwydmanski/rl_tennis

Continuous control with deep reinforcement learning

https://github.com/wyndwarrior/imitation_from_observation

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/xacheng1996/vfd

The DeepFake Detection Challenge (DFDC) Dataset

https://github.com/xalanq/chinese-sentiment-classification

A Structured Self-attentive Sentence Embedding

https://github.com/xbpeng/awr

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

https://github.com/xcmyz/Face-Binary-Classification

Deep Residual Learning for Image Recognition

https://github.com/xcmyz/FaceDetection

Deep Residual Learning for Image Recognition

https://github.com/xcmyz/Face_Binary_Classfication

Deep Residual Learning for Image Recognition

https://github.com/xg416/DATUM

Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset

https://github.com/xg416/mambatm

Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset

https://github.com/xhlulu/arxiv-assistant

Deep Residual Learning for Image Recognition

https://github.com/xialuxi/arcface-caffe

Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks

https://github.com/xiamenwcy/extended-caffe

Focal Loss for Dense Object Detection

https://github.com/xiaoccer/mobilefacenet_pytorch

MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices

https://github.com/xiaoxiong74/face-cluster-by-infomap

Learning to Cluster Faces on an Affinity Graph

https://github.com/xiaoyufenfei/LEDNet

Deep Residual Learning for Image Recognition

https://github.com/xiawenwen49/ppo

Proximal Policy Optimization Algorithms

https://github.com/xilinx/finn-examples

BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and Positioning Predictor on Edge Devices

https://github.com/xingyu-lin/softagent

Learning Latent Dynamics for Planning from Pixels

https://github.com/xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters

Deep Residual Learning for Image Recognition

https://github.com/xiuyu0000/new_papers_codes/tree/main/ppo

Proximal Policy Optimization Algorithms

https://github.com/xiuyu0000/new_papers_codes/tree/main/sac

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

https://github.com/xiuyu0000/papers_with_examples/tree/main/cancer_detection_demo

Deep Residual Learning for Image Recognition

https://github.com/xiuyu0000/papers_with_examples/tree/main/pfld

PFLD: A Practical Facial Landmark Detector

https://github.com/xiuyu0000/tutorials/tree/main/resnet

Deep Residual Learning for Image Recognition

https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/resnet.py

Deep Residual Learning for Image Recognition

https://github.com/xiuyu0000/vision/blob/main/mindvision/classification/models/vgg.py

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/xiuyu0000/vision/blob/main/mindvision/ms3d/models/pointnet2cls.py

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

https://github.com/xmu-xiaoma666/External-Attention-pytorch

RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition

https://github.com/xmu-xiaoma666/RepMLP-pytorch

RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition

https://github.com/xslidi/EfficientNets_ddl_apex

Deep Residual Learning for Image Recognition

https://github.com/xtma/simple-pytorch-rl

Continuous control with deep reinforcement learning

https://github.com/xuanyuzhou98/SqueezeSeg

Focal Loss for Dense Object Detection

https://github.com/xufanxiong/classification-of-caltech-256

Deep Residual Learning for Image Recognition

https://github.com/xurui1217/pointnet.pytorch-master

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

https://github.com/xuyuandong/simple-ddpg

Continuous control with deep reinforcement learning

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