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Autonomous Vehicles

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하위 태스크: 15
평가표: 1
보존된 평가 기록: 2

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

<span style="color:grey; opacity: 0.6">( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )</span>

코드

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

https://github.com/poojabhore12/SocialDistancing-Detector

YOLOv3: An Incremental Improvement

https://github.com/ppokhare/Handling-Imbalanced-Dataset-for-classification-task

Focal Loss for Dense Object Detection

https://github.com/ppriyank/MicronNet

MicronNet: A Highly Compact Deep Convolutional Neural Network Architecture for Real-time Embedded Traffic Sign Classification

https://github.com/prajjwal1/autonomous-object-detection

IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments

https://github.com/pranit570/salientobjectsdetection

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

https://github.com/pratibhaareddy/selfdrivingcar

End to End Learning for Self-Driving Cars

https://github.com/pratikshaya/image-data-augmentation-for-object-detection

Feature Pyramid Networks for Object Detection

https://github.com/preetam1997/Self-Driven-Car

End to End Learning for Self-Driving Cars

https://github.com/pritish-mahajan/Apricitas

YOLOv3: An Incremental Improvement

https://github.com/priyankadeybhadra/CNN-on-CIFR

Densely Connected Convolutional Networks

https://github.com/priyavrat-misra/xrays-and-gradcam

Deep Residual Learning for Image Recognition

https://github.com/probabilistic-jsma/probabilistic-jsma

Probabilistic Jacobian-based Saliency Maps Attacks

https://github.com/programmingLearner/MATF-architecture-details

Multi-Agent Tensor Fusion for Contextual Trajectory Prediction

https://github.com/prximenes/2D-CNN-IDS-FOR-IVNs

Convolutional Neural Network-based Intrusion Detection System for AVTP Streams in Automotive Ethernet-based Networks

https://github.com/przszczecinski/AirSim

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

https://github.com/pszemraj/BoulderAreaDetector

Deep Residual Learning for Image Recognition

https://github.com/pudae/tensorflow-densenet

Densely Connected Convolutional Networks

https://github.com/pulp-platform/Himax_Dataset

A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

https://github.com/purduedigitaltwin/talk2drive

Personalized Autonomous Driving with Large Language Models: Field Experiments

https://github.com/purewater0901/carCalibration

Baidu Apollo Auto-Calibration System - An Industry-Level Data-Driven and Learning based Vehicle Longitude Dynamic Calibrating Algorithm

https://github.com/puyuan1996/MARL

Counterfactual Multi-Agent Policy Gradients

https://github.com/pyaf/DenseNet-MURA-PyTorch

Densely Connected Convolutional Networks

https://github.com/pytorch/vision

Deep Residual Learning for Image Recognition

https://github.com/pytorch/vision/blob/main/torchvision/models/densenet.py

Densely Connected Convolutional Networks

https://github.com/qiaozhijian/vLPD-Net

A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition

https://github.com/qingyujean/Classification-on-imbalanced-data

Focal Loss for Dense Object Detection

https://github.com/qiyan98/social-nce-stgcnn

Social NCE: Contrastive Learning of Socially-aware Motion Representations

https://github.com/qqwweee/keras-yolo3

YOLOv3: An Incremental Improvement

https://github.com/quan-dao/practical-collab-perception

MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences

https://github.com/quangvy2703/ABCNet-ESRGAN-SRTEXT

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/qubvel/efficientnet

Deep Residual Learning for Image Recognition

https://github.com/qubvel/resnet_152

Deep Residual Learning for Image Recognition

https://github.com/qwenlm/qwen2-vl

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

https://github.com/qy1994-0919/cfpnet

YOLOX: Exceeding YOLO Series in 2021

https://github.com/r06942054/NOTE-RCNN

Feature Pyramid Networks for Object Detection

https://github.com/rafa2000/Top-TensorFlow

End to End Learning for Self-Driving Cars

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