Papers with Code 아카이브
Autonomous Vehicles
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/dc17540/darknet
https://github.com/dead-mazai/avia-missing-airplanes
https://github.com/deepcs233/visual-cot
LMDrive: Closed-Loop End-to-End Driving with Large Language Models
https://github.com/deeplearnproject/darknet
https://github.com/deepmind/dm-haiku
https://github.com/deepmodeling/deepmd-kit
https://github.com/deepquestai/fire-smoke-dataset
https://github.com/deepsense-ai/carla-birdeye-view
Simulation-based reinforcement learning for real-world autonomous driving
https://github.com/deepsense-ai/carla-real-traffic-scenarios
https://github.com/delmalih/MIAS-mammography-obj-detection
https://github.com/demul/ResidualNet
https://github.com/demul/image_segmentation_project
A Review on Deep Learning Techniques Applied to Semantic Segmentation
https://github.com/deontaepharr/Residual-Attention-Network
https://github.com/destinyls/SMOKE
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
https://github.com/detectionteamucas/retinanet_tensorflow
https://github.com/devansh20la/VisualBackprop
https://github.com/dianzl/sodformer
https://github.com/diggs1711/comma-ai-speed-challenge
https://github.com/dineshresearch/Novel-Deep-Learning-Model-for-Traffic-Sign-Detection-Using-Capsule-Networks
Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks
https://github.com/dipuchak95/dip_net
https://github.com/dishen12/py03
https://github.com/divyakraman/Domain-Adaptive-Knowledge-Distillation-for-Driving-Scene-Semantic-Segmentation
Domain Adaptive Knowledge Distillation for Driving Scene Semantic Segmentation
https://github.com/divyakraman/SAfE-Self-Attention-Based-Unsupervised-Road-Safety-Classification-in-Hazardous-Environments
https://github.com/divyakraman/SS-SFDA-Self-Supervised-Source-Free-Domain-Adaptation-for-Road-Segmentation-in-Hazardous-Environme
https://github.com/dmizr/phuber
https://github.com/dnddnjs/pytorch-cifar10
https://github.com/dnjs3594/Eigencontours
Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes
https://github.com/dnozza/profanity-obfuscation
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/dorbodwolf/darknet
https://github.com/dronefreak/dji-tello-collision-avoidance-pydnet
Towards real-time unsupervised monocular depth estimation on CPU
https://github.com/drtupe/Behavioral_Cloning
https://github.com/dssbxx/k_labels_resnet50
https://github.com/dtc111111/multi-modal-uav
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM
https://github.com/dtthi/darknetAlexeyAB
https://github.com/duchaba/Norwegian_Blue_Parrot_k2fa_AI
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.