Search results with tag "Visual recognition"
Deep Learning for Generic Object Detection: A Survey
link.springer.comLarge Scale Visual Recognition Challenge (ILSVRC) (Rus-sakovsky et al. 2015). Since that time, the research focus in ... as visual recognition, object detection, speech recognition, ... instance level recognition − 2017 ICCV17 A short course of recent advances
Rich Feature Hierarchies for Accurate Object Detection and ...
openaccess.thecvf.comvisual recognition tasks has been based considerably on the use of SIFT [26] and HOG [7]. But if we look at perfor-mance on the canonical visual recognition task, PASCAL VOC object detection [12], it is generally acknowledged that progress has been slow during 2010-2012, with small gains obtained by building ensemble systems and employ-
Involution: Inverting the Inherence of Convolution for ...
arxiv.orgness for visual recognition as an alternative, breaking through existing inductive biases of convolution. 2.We bridge the emerging philosophy of incorporating self-attention into the learning procedure of visual rep-resentation. In this context, the desiderata of com-posing pixel pairs for relation modeling is challenged.
ImageNet: A Large-Scale Hierarchical Image Database
www-cs.stanford.edushow that ImageNet is a large-scale, accurate and diverse image database (Section2). In Section4, we present a few simple application examples by exploiting the current Ima-geNet, mostly the mammal and vehicle subtrees. Our goal is to show that ImageNet can serve as a useful resource for visual recognition applications such as object recognition,
Class-Balanced Loss Based on Effective Number of Samples
openaccess.thecvf.comand large-scale datasets including ImageNet and iNatural-ist. Our results show that when trained with the proposed class-balanced loss, the network is able to achieve signifi-cant performance gains on long-tailed datasets. 1. Introduction The recent success of deep Convolutional Neural Net-works (CNNs) for visual recognition [26, 37, 38, 16] owes