160 citations · 611 across the 21 of their papers we have counts for
6 papers · 1 filter
Hierarchy-Dependent Cross-Platform Multi-View Feature Learning for Venue Category Prediction
Shuqiang Jiang, Weiqing Min, Shuhuan Mei
In this work, we focus on visual venue category prediction, which can facilitate various applications for location-based service and personalization. Considering that the complemen…
Learning Effective RGB-D Representations for Scene Recognition
Xinhang Song, Shuqiang Jiang, Luis Herranz +1
Deep convolutional networks (CNN) can achieve impressive results on RGB scene recognition thanks to large datasets such as Places. In contrast, RGB-D scene recognition is still und…
A Survey on Food Computing
Weiqing Min, Shuqiang Jiang, Linhu Liu +2
Food is very essential for human life and it is fundamental to the human experience. Food-related study may support multifarious applications and services, such as guiding the huma…
Food recognition and recipe analysis: integrating visual content, context and external knowledge
Luis Herranz, Weiqing Min, Shuqiang Jiang
The central role of food in our individual and social life, combined with recent technological advances, has motivated a growing interest in applications that help to better monito…
Scene recognition with CNNs: objects, scales and dataset bias
Luis Herranz, Shuqiang Jiang, Xiangyang Li
Since scenes are composed in part of objects, accurate recognition of scenes requires knowledge about both scenes and objects. In this paper we address two related problems: 1) sca…
Depth CNNs for RGB-D scene recognition: learning from scratch better than transferring from RGB-CNNs
Xinhang Song, Luis Herranz, Shuqiang Jiang
Scene recognition with RGB images has been extensively studied and has reached very remarkable recognition levels, thanks to convolutional neural networks (CNN) and large scene dat…