Pedestrian detection is a key problem in computer vision, with several applications that have the potential to positively impact quality of life. In recent years, the number of approaches to …
Abstract We propose'Hide-and-Seek', a weakly-supervised framework that aims to improve object localization in images and action localization in videos. Most existing weakly …
M Noroozi, P Favaro - European conference on computer vision, 2016 - Springer
We propose a novel unsupervised learning approach to build features suitable for object detection and classification. The features are pre-trained on a large dataset without human …
In recent years, deep learning-based algorithms have brought great improvements to rigid object detection. In addition to rigid objects, remote sensing images also contain many …
Y Tian, B Fan, F Wu - … of the IEEE conference on computer …, 2017 - openaccess.thecvf.com
The research focus of designing local patch descriptors has gradually shifted from handcrafted ones (eg, SIFT) to learned ones. In this paper, we propose to learn high per …
J Tang, C Deng, GB Huang - IEEE transactions on neural …, 2015 - ieeexplore.ieee.org
Extreme learning machine (ELM) is an emerging learning algorithm for the generalized single hidden layer feedforward neural networks, of which the hidden node parameters are …
T Wang, Z Zheng, C Yan, J Zhang… - … on Circuits and …, 2021 - ieeexplore.ieee.org
Cross-view geo-localization is to spot images of the same geographic target from different platforms, eg, drone-view cameras and satellites. It is challenging in the large visual …
Successful visual object recognition methods typically rely on training datasets containing lots of richly annotated images. Annotating object bounding boxes is both expensive and …