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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 Tomiyama , Pixel Feature Alignment Network , Ritsumeikan University , Ritsumeikan University Research , Towards More Accurate , Object Detection , Professor Hiroyuki Tomiyama , Point Pixel Feature Alignment , Things Journal , Memory Based Point Pixel Fusion , Deformable Point Pixel Fusion , Semantic Alignment Evaluator , Dynamic Point Pixel Feature Alignment , University Research Report ,