168 citations · 726 across the 30 of their papers we have counts for
6 papers · 1 filter
Single-Shot Object Detection with Enriched Semantics
Zhishuai Zhang, Siyuan Qiao, Cihang Xie +3
We propose a novel single shot object detection network named Detection with Enriched Semantics (DES). Our motivation is to enrich the semantics of object detection features within…
Gradually Updated Neural Networks for Large-Scale Image Recognition
Siyuan Qiao, Zhishuai Zhang, Wei Shen +2
Depth is one of the keys that make neural networks succeed in the task of large-scale image recognition. The state-of-the-art network architectures usually increase the depths by c…
Few-shot Learning by Exploiting Visual Concepts within CNNs
Boyang Deng, Qing Liu, Siyuan Qiao +1
Convolutional neural networks (CNNs) are one of the driving forces for the advancement of computer vision. Despite their promising performances on many tasks, CNNs still face major…
Few-Shot Image Recognition by Predicting Parameters from Activations
Siyuan Qiao, Chenxi Liu, Wei Shen +1
In this paper, we are interested in the few-shot learning problem. In particular, we focus on a challenging scenario where the number of categories is large and the number of examp…
ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond
Siyuan Qiao, Wei Shen, Weichao Qiu +2
Motivated by product detection in supermarkets, this paper studies the problem of object proposal generation in supermarket images and other natural images. We argue that estimatio…
SORT: Second-Order Response Transform for Visual Recognition
Yan Wang, Lingxi Xie, Chenxi Liu +3
In this paper, we reveal the importance and benefits of introducing second-order operations into deep neural networks. We propose a novel approach named Second-Order Response Trans…