Autonomous Vehicles
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/liuyuan000/yolox_sar
https://github.com/liuzhuang13/DenseNetCaffe
https://github.com/livox-sdk/livox_detection
https://github.com/lixihan/Resnet
https://github.com/lixixibj/forecasting-with-time-series-imaging
https://github.com/lixixibj/tsImage-forecasting
https://github.com/liyemei/Deformable-active-convolutional
https://github.com/lizonghang/leaf-mx
https://github.com/ljy-hy/mentormix_pytorch
https://github.com/lkeonwoo94/DL_cv-mdt_NVIDIA_Cert_Course_StudyPI
https://github.com/llmbev/talk2bev
Talk2BEV: Language-enhanced Bird's-eye View Maps for Autonomous Driving
https://github.com/llsouder/screen-ocr
https://github.com/lly00412/sednet
https://github.com/lmeulen/PeopleCounter
https://github.com/loadbxh/yolov3
https://github.com/lobznet/yolov3
https://github.com/lojzezust/WaSR
A water-obstacle separation and refinement network for unmanned surface vehicles
https://github.com/long95288/car-logo-detect
https://github.com/lorebianchi98/fg-ovd
Is CLIP the main roadblock for fine-grained open-world perception?
https://github.com/louisccc/sg-risk-assessment
Scene-Graph Augmented Data-Driven Risk Assessment of Autonomous Vehicle Decisions
https://github.com/lpiccinelli-eth/unidepth
iDisc: Internal Discretization for Monocular Depth Estimation
https://github.com/lpirola13/flower-recognizer
https://github.com/lpirola13/flower_recognizer
https://github.com/lrf008/yolov4
https://github.com/lrxiao/free-space
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
https://github.com/ls-da3m0ns/Short-ResNet
https://github.com/ltriess/kitti_scan_unfolding
Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study
https://github.com/luckymanwu/defect_detection
https://github.com/luigiluz/cnn-ids-for-avtp-networks-reproduction
https://github.com/lvweiwolf/efficientdet
https://github.com/lxy000719/ResNet-50-pneumonia-classification
https://github.com/lyffly/Python-3DPointCloud-and-RGBD
https://github.com/lyffly/YOLOv3_with_my_Dataset
https://github.com/lyk19940625/MyRFBNet
https://github.com/lzrobots/dgmn
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.