We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Object detection and recognition has achieved a significant progress in recent years. However robust 3D object detection and segmentation in noisy 3D data volumes remains a challen...
Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang...
Given a set of 3D model features and their 2D image, model based object recognition determines the correspondences between those features and hence computes the pose of the object...
In order to deploy mobile robots in social environments like indoor buildings, they need to be provided with perceptual abilities to detect people. In the computer vision literatur...