Tutorial: Point cloud library: Three-dimensional object recognition and 6 dof pose estimation
Tutorial: Point Cloud Library: Three-Dimensional Object Recognition and 6 DOF Pose Estimation
Page 1 Point Cloud Library Three-Dimensional Object Recognition and 6 DoF Pose Estimation …
Page 1 Point Cloud Library Three-Dimensional Object Recognition and 6 DoF Pose Estimation …
Aggregating local deep features for image retrieval
A Babenko, V Lempitsky - Proceedings of the IEEE …, 2015 - openaccess.thecvf.com
Several recent works have shown that image descriptors produced by deep convolutional
neural networks provide state-of-the-art performance for image classification and retrieval …
neural networks provide state-of-the-art performance for image classification and retrieval …
Image classification with the fisher vector: Theory and practice
A standard approach to describe an image for classification and retrieval purposes is to
extract a set of local patch descriptors, encode them into a high dimensional vector and pool …
extract a set of local patch descriptors, encode them into a high dimensional vector and pool …
Improving the fisher kernel for large-scale image classification
The Fisher kernel (FK) is a generic framework which combines the benefits of generative
and discriminative approaches. In the context of image classification the FK was shown to …
and discriminative approaches. In the context of image classification the FK was shown to …
A large-scale hierarchical multi-view rgb-d object dataset
Over the last decade, the availability of public image repositories and recognition
benchmarks has enabled rapid progress in visual object category and instance detection …
benchmarks has enabled rapid progress in visual object category and instance detection …
[PDF][PDF] Aggregating deep convolutional features for image retrieval
A Babenko, V Lempitsky - arXiv preprint arXiv:1510.07493, 2015 - cv-foundation.org
Several recent works have shown that image descriptors produced by deep convolutional
neural networks provide state-of-the-art performance for image classification and retrieval …
neural networks provide state-of-the-art performance for image classification and retrieval …
Convolutional kernel networks
An important goal in visual recognition is to devise image representations that are invariant
to particular transformations. In this paper, we address this goal with a new type of …
to particular transformations. In this paper, we address this goal with a new type of …
Remote Sensing Image Interpretation: Deep Belief Networks for Multi-Object Analysis
Object Classification in Remote Sensing Imagery holds paramount importance for extracting
meaningful insights from complex aerial scenes. Conventional methods encounter …
meaningful insights from complex aerial scenes. Conventional methods encounter …
Semantic segmentation with second-order pooling
J Carreira, R Caseiro, J Batista… - Computer Vision–ECCV …, 2012 - Springer
Feature extraction, coding and pooling, are important components on many contemporary
object recognition paradigms. In this paper we explore novel pooling techniques that …
object recognition paradigms. In this paper we explore novel pooling techniques that …
Efficient additive kernels via explicit feature maps
A Vedaldi, A Zisserman - IEEE transactions on pattern analysis …, 2012 - ieeexplore.ieee.org
Large scale nonlinear support vector machines (SVMs) can be approximated by linear ones
using a suitable feature map. The linear SVMs are in general much faster to learn and …
using a suitable feature map. The linear SVMs are in general much faster to learn and …