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Towards More Accurate 3D Object Detection for Robots and Self-Driving Cars

Towards More Accurate 3D Object Detection for Robots and Self-Driving Cars
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Hiroyuki tomiyamaCollege of sciencePixel feature alignment networkRitsumeikan universityRitsumeikan university researchKyushu universityProfessor hiroyuki tomiyamaPoint pixel feature alignmentThings journalMemory based point pixel fusionDeformable point pixel fusionSemantic alignment evaluatorDynamic point pixel feature alignmentUniversity research reportProject number

DPPFA−Net Enhances 3D Object Detection for Autonomous Systems

Synopsis:Ritsumeikan University researchers introduce DPPFA−Net, a groundbreaking 3D object detection network melding LiDAR and image data to improve accuracy f

Hiroyuki tomiyamaRitsumeikan universityProfessor hiroyuki tomiyamaMemory based point pixel fusionDeformable point pixel fusionSemantic alignment evaluator

Network combines 3D LiDAR and 2D image data to enable more robust detection of small objects

Network combines 3D LiDAR and 2D image data to enable more robust detection of small objects
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Hiroyuki tomiyamaJuncheng wangRitsumeikan universityPixel feature alignment networkProfessor hiroyuki tomiyamaPoint pixel feature alignmentMemory based point pixel fusionDeformable point pixel fusionSemantic alignment evaluatorDynamic point pixel feature alignmentObject detectionThings journal

Towards More Accurate 3D Object Detection for Robots and Self-Driving Cars

Robots and autonomous vehicles can use 3D point clouds from LiDAR sensors and camera images to perform 3D object detection. However, current techniques that combine both types of data struggle to accurately detect small objects. Now, researchers from Japan have developed DPPFA−Net, an innovative network that overcomes challenges related to occlusion and noise introduced by…

Hiroyuki tomiyamaPixel feature alignment networkRitsumeikan universityRitsumeikan university researchTowards more accurateObject detectionProfessor hiroyuki tomiyamaPoint pixel feature alignmentThings journalMemory based point pixel fusionDeformable point pixel fusionSemantic alignment evaluatorDynamic point pixel feature alignmentUniversity research report

Advancements in 3D Object Detection for Robots, Self-Driving Cars

Advancements in 3D Object Detection for Robots, Self-Driving Cars
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Hiroyuki tomiyamaKyushu universityRitsumeikan universityRitsumeikan university researchPixel feature alignment networkCollege of scienceProfessor hiroyuki tomiyamaPoint pixel feature alignmentThings journalMemory based point pixel fusionDeformable point pixel fusionSemantic alignment evaluatorUniversity research reportProject number