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Self-Driving Cars

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Self-driving cars : the task of making a car that can drive itself without human guidance.

<span style="color:grey; opacity: 0.6">( Image credit: Learning a Driving Simulator )</span>

코드

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

https://github.com/eric-mitchell/serac

Editable Neural Networks

https://github.com/ermolenkodev/keras-salient-object-visualisation

Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car

https://github.com/ethanmclark1/carla_aebs

End to End Learning for Self-Driving Cars

https://github.com/gaozhitong/atta

Scaling Out-of-Distribution Detection for Real-World Settings

https://github.com/gdineshk6174/self-driving-car

End to End Learning for Self-Driving Cars

https://github.com/gitliber/Basic_self_driving_car

End to End Learning for Self-Driving Cars

https://github.com/giusenso/seld-tcn

SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks

https://github.com/govardhanharish/selfDriving

End to End Learning for Self-Driving Cars

https://github.com/greerviau/GlorifiedCruiseControl

End to End Learning for Self-Driving Cars

https://github.com/griffinbran/Democratizing-Autonomous-Driving

End to End Learning for Self-Driving Cars

https://github.com/griffinbran/machines_best_friend

VisualBackProp: efficient visualization of CNNs

https://github.com/hamidmousavi0/reliable-relu-toolbox

FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions

https://github.com/harshayugirase/human-path-prediction

It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction

https://github.com/heechul/picar

End to End Learning for Self-Driving Cars

https://github.com/henry1iu/tnt-trajectory-prediction

VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation

https://github.com/huang-xx/STGAT

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

https://github.com/huangchaoxing/8536-project

End to End Learning for Self-Driving Cars

https://github.com/huangchaoxing/Deep-Learning-Pilot---GTA-V

End to End Learning for Self-Driving Cars

https://github.com/iPhoring/BehavioralCloning

End to End Learning for Self-Driving Cars

https://github.com/inhwanbae/npsn

It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction

https://github.com/intel/ad-rss-lib

On a Formal Model of Safe and Scalable Self-driving Cars

https://github.com/inverted-ai/torchdrivesim

Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation

https://github.com/jaganadhg/tf2x_eval

End to End Learning for Self-Driving Cars

https://github.com/jeapostrophe/monaco

A0C: Alpha Zero in Continuous Action Space

https://github.com/jm12138/car-behavioral-cloning-paddle

End to End Learning for Self-Driving Cars

https://github.com/kaycee-agent/End-to-End-Self-Driving-via-CNN

End to End Learning for Self-Driving Cars

https://github.com/kingjamessong/rankfeat

Scaling Out-of-Distribution Detection for Real-World Settings

https://github.com/kirilcvetkov92/Self-Driving-Car-Behavior-Deep-Learning

End to End Learning for Self-Driving Cars

https://github.com/kodluyoruz-ML-bootcamp-1/BSSA

End to End Learning for Self-Driving Cars

https://github.com/koolhussain/Self-Driving-Car

End to End Learning for Self-Driving Cars

https://github.com/lekhraj-d/Self-Drive-Car-Implemention-Using-Keras

End to End Learning for Self-Driving Cars

https://github.com/lh-wang/ACC

End to End Learning for Self-Driving Cars

https://github.com/littlemountainman/selfdrive

End to End Learning for Self-Driving Cars

https://github.com/m-hasan-n/pooling

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

https://github.com/madhuridhangar/Self_Driving_Car

End to End Learning for Self-Driving Cars

https://github.com/manish-vi/Autopilot-Tensoflow

End to End Learning for Self-Driving Cars

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