Papers with Code 아카이브
Sensor Fusion
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Sensor fusion is the process of combining sensor data or data derived from disparate sources such that the resulting information has less uncertainty than would be possible when these sources were used individually. [Wikipedia]
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AmrElsersy/PointPainting
https://github.com/Avinash2468/RackLay
https://github.com/CogRob/distributed-mapper
https://github.com/DTU-PAS/awesome-dynn-for-cv
A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor Fusion
https://github.com/GatorSense/MICI
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty
https://github.com/HengWeiBin/CenterFusionDetect3D
CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection
https://github.com/JrkJamie/eagermot_ms
https://github.com/Kin-Zhang/mmfn
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
https://github.com/MindSpore-scientific-2/code-10/tree/main/STCrowd
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
https://github.com/MindSpore-scientific-2/code-11/tree/main/STCrowd
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
https://github.com/MindSpore-scientific-2/code-8/tree/main/STCrowd
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
https://github.com/Nik-V9/HEAPUtil
Hierarchical Multi-Process Fusion for Visual Place Recognition
https://github.com/Rabeea369/latte
https://github.com/Radar-Camera-Fusion/Awesome-Radar-Perception
https://github.com/Song-Jingyu/PointPainting
https://github.com/UMich-BipedLab/AprilTag_ROS
https://github.com/UMich-BipedLab/ROB101-ExtrinsicCalibrationProblem
https://github.com/UMich-BipedLab/automatic_lidar_camera_calibration
https://github.com/UMich-BipedLab/lidar_simulator
https://github.com/UMich-BipedLab/sync_lidartag_apriltag
https://github.com/aliansgp/RL-SAC-CARLA
Autonomous Driving using Residual Sensor Fusion and Deep Reinforcement Learning
https://github.com/autonomousvision/navsim
TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
https://github.com/czarmanu/deeplab-lakeice-webcams
Learning a Joint Embedding of Multiple Satellite Sensors: A Case Study for Lake Ice Monitoring
https://github.com/czarmanu/sentinel_lakeice
Learning a Joint Embedding of Multiple Satellite Sensors: A Case Study for Lake Ice Monitoring
https://github.com/fsalmasri/MSF-STI-SR
Multimodal Sensor Fusion In Single Thermal image Super-Resolution
https://github.com/hbutsuak95/monolayout
https://github.com/hitachi-rd-cv/mmac_captions
Sensor-Augmented Egocentric-Video Captioning with Dynamic Modal Attention
https://github.com/hkust-aerial-robotics/vins-fisheye
A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors
https://github.com/hvak/mimrf-bfm
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty
https://github.com/hyye/lio-mapping
https://github.com/ken-power/SensorFusionND-3D-Object-Tracking
https://github.com/mialbro/PointFusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/mialbro/pytorch_pointfusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/mshn2000/PointFusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/ngowilliam1/centerfusion_depth_factor
CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.