Multi-view object detection or the problem of detecting an object using multiple viewpoints, is
an important problem in computer vision with varied applications such as distributed smart …

Incorporating multiple camera views for detection alleviates the impact of occlusions in
crowded scenes. In a multiview detection system, we need to answer two important …

A multi-view object detection approach based on deep learning is proposed in this paper.
Classical object detection methods based on regression models are introduced, and the …

Multiview detection incorporates multiple camera views to deal with occlusions, and its
central problem is multiview aggregation. Given feature map projections from multiple views …

Multi-view detection incorporates multiple camera views to alleviate occlusion in crowded
scenes, where the state-of-the-art approaches adopt homography transformations to project …

Active vision is a desirable perceptual feature for robots. Existing approaches usually make
strong assumptions about the task and environment, thus are less robust and efficient. This …

In this paper we propose an end-to-end learnable approach that detects static urban objects
from multiple views, re-identifies instances, and finally assigns a geographic position per …

Multi-view object detection is challenging due to the influence of the different view-angles on
intra-class similarity. The uniformed feature representation of traditional detectors couples …

Humans' decision making process often relies on utilizing visual information from different
views or perspectives. However, in machine-learning-based image classification we …

Despite the commercial abundance of UAVs aerial data acquisition remains challenging
and the existing Asia and North America-centric open-source UAV datasets are small-scale …