C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
Gibson Environments: Real-World Perception for Embodied Agents
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
IROS 2020 se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
Código oficial: Aprendizaje de orientación 3D implícita para la detección de objetos 6D a partir de imágenes RGB
Las características principales de dlr-rm/augmentedautoencoder son: Perception and Machine Learning, Percepción y seguimiento.
Las alternativas de código abierto para dlr-rm/augmentedautoencoder incluyen: stanfordvl/gibsonenv — Gibson Environments: Real-World Perception for Embodied Agents. wkentaro/morefusion — MoreFusion: Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion, CVPR 2020. appinho/sarosperceptionkitti — ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark… praveen-palanisamy/multiple-object-tracking-lidar — C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud. wenbowen123/iros20-6d-pose-tracking — [IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains. deap/deap.