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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/ahq1993/MPNet

Motion Planning Networks

https://github.com/akshaybahadur21/Autopilot

End to End Learning for Self-Driving Cars

https://github.com/aliansgp/RL-SAC-CARLA

Autonomous Driving using Residual Sensor Fusion and Deep Reinforcement Learning

https://github.com/amalbros/Self-Driving-Car-Simulation

End to End Learning for Self-Driving Cars

https://github.com/ameyskulkarni/End-to-End-Learning-for-Steering-Angle-Prediction

End to End Learning for Self-Driving Cars

https://github.com/amiryanj/socialways

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

https://github.com/anasbadawy/Steering-Prediction-CNN

End to End Learning for Self-Driving Cars

https://github.com/anirudh9784/Adversarial-Defense

An integrated Auto Encoder-Block Switching defense approach to prevent adversarial attacks

https://github.com/anuragranj/flowattack

Attacking Optical Flow

https://github.com/aravindmanoharan/Self-Driving-Car-V1

End to End Learning for Self-Driving Cars

https://github.com/aravindmanoharan/Self-Driving-Car-V2

End to End Learning for Self-Driving Cars

https://github.com/arief25ramadhan/udacity-behavioral-cloning

End to End Learning for Self-Driving Cars

https://github.com/as1067/PiCar

End to End Learning for Self-Driving Cars

https://github.com/ashutosh1997/Self_Driving_Car

End to End Learning for Self-Driving Cars

https://github.com/ashutoshkumar19/Self_Driving_Car

End to End Learning for Self-Driving Cars

https://github.com/atlas604/behavioral-cloning

End to End Learning for Self-Driving Cars

https://github.com/berkcomba/Self-Driving-Car-Keras

End to End Learning for Self-Driving Cars

https://github.com/bobbyhaliwela/AutoRcCar

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

https://github.com/bobbyhaliwela/AutoRcCar-Behavioral-Clonning

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

https://github.com/charusharma1991/SSL_PointClouds

Self-Supervised Few-Shot Learning on Point Clouds

https://github.com/chenfengxu714/image2point

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

https://github.com/chingisooinar/End-to-End-Deep-Learning-Approach-for-Autonomous-Driving-DuckieTown

End to End Learning for Self-Driving Cars

https://github.com/chuanhaoliu/CarND-Behavioral-Cloning

End to End Learning for Self-Driving Cars

https://github.com/clarky104/carla_aebs

End to End Learning for Self-Driving Cars

https://github.com/cmubig/SPEC

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

https://github.com/code-implementation1/Code6/tree/main/OctSqueeze

OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression

https://github.com/commaai/research

Learning a Driving Simulator

https://github.com/crearth/ai

Learning a Driving Simulator

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

End to End Learning for Self-Driving Cars

https://github.com/dawn360/Behavioral-Cloning-P3

End to End Learning for Self-Driving Cars

https://github.com/devansh20la/VisualBackprop

VisualBackProp: efficient visualization of CNNs

https://github.com/diggs1711/comma-ai-speed-challenge

End to End Learning for Self-Driving Cars

https://github.com/drtupe/Behavioral_Cloning

End to End Learning for Self-Driving Cars

https://github.com/dwiggles/AIX360-withdata

Leveraging Latent Features for Local Explanations

https://github.com/ee17b031-iittp/MNIST-Retrain-with-DeepXplore

DeepXplore: Automated Whitebox Testing of Deep Learning Systems

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

Editable Neural Networks

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