Real-Time Object Pose Estimation with Pose Interpreter Networks
In this work, we introduce pose interpreter networks for 6-DoF object pose estimation. In contrast to other CNN-based approaches to pose estimation that require expensively annotated object pose data, our pose interpreter network is trained entirely on synthetic pose data. We use object masks as an intermediate representation to bridge real and synthetic. We show that when combined with a segmentation model trained on RGB images, our synthetically trained pose interpreter network is able to generalize to real data. Our end-to-end system for object pose estimation runs in real-time (20 Hz) on live RGB data, without using depth information or ICP refinement.
Code (2)
Tasks
ObjectPose EstimationSimilar Papers 제목 키워드 기반
Towards real-time object recognition and pose estimation in point clouds
Object recognition and 6DoF pose estimation are quite challenging tasks in computer vision applications. Despite efficiency in such tasks, standard methods deliver far from real-time processing rates. This paper presents…
Objectobject-detectionObject DetectionObject Recognition+1Real-time Light Estimation and Neural Soft Shadows for AR Indoor Scenarios
We present a pipeline for realistic embedding of virtual objects into footage of indoor scenes with focus on real-time AR applications. Our pipeline consists of two main components: A light estimator and a neural soft sh…
SMOC-Net: Leveraging Camera Pose for Self-Supervised Monocular Object Pose Estimation
Recently, self-supervised 6D object pose estimation, where synthetic images with object poses (sometimes jointly with un-annotated real images) are used for training, has attracted much attention in computer vision. …
6D Pose Estimation using RGBKnowledge DistillationObjectPose Estimation+1Sparse Color-Code Net: Real-Time RGB-Based 6D Object Pose Estimation on Edge Devices
As robotics and augmented reality applications increasingly rely on precise and efficient 6D object pose estimation, real-time performance on edge devices is required for more interactive and responsive systems. Our prop…
6D Pose Estimation using RGBObjectPose EstimationSegICP: Integrated Deep Semantic Segmentation and Pose Estimation
Recent robotic manipulation competitions have highlighted that sophisticated robots still struggle to achieve fast and reliable perception of task-relevant objects in complex, realistic scenarios. To improve these system…
Object RecognitionPoint Cloud RegistrationPose EstimationPosition+1