160 citations · 611 across the 21 of their papers we have counts for
23 papers
GridMM: Grid Memory Map for Vision-and-Language Navigation
Zihan Wang, Xiangyang Li, Jiahao Yang +2
Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments. To represent the previously v…
A Cross-direction Task Decoupling Network for Small Logo Detection
Hou, Sujuan, Li +10
Logo detection plays an integral role in many applications. However, handling small logos is still difficult since they occupy too few pixels in the image, which burdens the extrac…
KERM: Knowledge Enhanced Reasoning for Vision-and-Language Navigation
Xiangyang Li, Zihan Wang, Jiahao Yang +2
Vision-and-language navigation (VLN) is the task to enable an embodied agent to navigate to a remote location following the natural language instruction in real scenes. Most of the…
Deep Learning for Logo Detection: A Survey
Sujuan Hou, Jiacheng Li, Weiqing Min +4
When logos are increasingly created, logo detection has gradually become a research hotspot across many domains and tasks. Recent advances in this area are dominated by deep learni…
Hierarchical Object-to-Zone Graph for Object Navigation
Sixian Zhang, Xinhang Song, Yubing Bai +3
The goal of object navigation is to reach the expected objects according to visual information in the unseen environments. Previous works usually implement deep models to train an…
FoodLogoDet-1500: A Dataset for Large-Scale Food Logo Detection via Multi-Scale Feature Decoupling Network
Qiang Hou, Weiqing Min, Jing Wang +3
Food logo detection plays an important role in the multimedia for its wide real-world applications, such as food recommendation of the self-service shop and infringement detection…
A review on vision-based analysis for automatic dietary assessment
Wei Wang, Weiqing Min, Tianhao Li +3
Background: Maintaining a healthy diet is vital to avoid health-related issues, e.g., undernutrition, obesity and many non-communicable diseases. An indispensable part of the healt…
Applications of knowledge graphs for food science and industry
Weiqing Min, Chunlin Liu, Leyi Xu +1
The deployment of various networks (e.g., Internet of Things [IoT] and mobile networks), databases (e.g., nutrition tables and food compositional databases), and social media (e.g.…
Large Scale Visual Food Recognition
Weiqing Min, Zhiling Wang, Yuxin Liu +5
Food recognition plays an important role in food choice and intake, which is essential to the health and well-being of humans. It is thus of importance to the computer vision commu…
Rethinking the Optimization of Average Precision: Only Penalizing Negative Instances before Positive Ones is Enough
Zhuo Li, Weiqing Min, Jiajun Song +5
Optimizing the approximation of Average Precision (AP) has been widely studied for image retrieval. Limited by the definition of AP, such methods consider both negative and positiv…
ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network
Weiqing Min, Linhu Liu, Zhiling Wang +4
Food recognition has received more and more attention in the multimedia community for its various real-world applications, such as diet management and self-service restaurants. A l…
LogoDet-3K: A Large-Scale Image Dataset for Logo Detection
Jing Wang, Weiqing Min, Sujuan Hou +3
Logo detection has been gaining considerable attention because of its wide range of applications in the multimedia field, such as copyright infringement detection, brand visibility…
Dataset Bias in Few-shot Image Recognition
Shuqiang Jiang, Yaohui Zhu, Chenlong Liu +3
The goal of few-shot image recognition (FSIR) is to identify novel categories with a small number of annotated samples by exploiting transferable knowledge from training data (base…
Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classification
Jing Wang, Weiqing Min, Sujuan Hou +4
Logo classification has gained increasing attention for its various applications, such as copyright infringement detection, product recommendation and contextual advertising. Compa…
Scene Recognition with Prototype-agnostic Scene Layout
Gongwei Chen, Xinhang Song, Haitao Zeng +1
Abstract--- Exploiting the spatial structure in scene images is a key research direction for scene recognition. Due to the large intra-class structural diversity, building and mode…
Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition
Xiangyang Li, Luis Herranz, Shuqiang Jiang
In recent years, convolutional neural networks (CNNs) have achieved impressive performance for various visual recognition scenarios. CNNs trained on large labeled datasets can not…
Food Recommendation: Framework, Existing Solutions and Challenges
Weiqing Min, Shuqiang Jiang, Ramesh Jain
A growing proportion of the global population is becoming overweight or obese, leading to various diseases (e.g., diabetes, ischemic heart disease and even cancer) due to unhealthy…
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…