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20202024
most citedASTRAL: Adversarial Trained LSTM-CNN for Named Entity Recognition

73 citations · 251 across the 20 of their papers we have counts for

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15 papers · 1 filter

cs.CV2024★ 34 cited

Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene Classification

Wenjia Xu, Jiuniu Wang, Zhiwei Wei +2

Deep neural networks have achieved promising progress in remote sensing (RS) image classification, for which the training process requires abundant samples for each class. However,…

cs.CV2023

ARAI-MVSNet: A multi-view stereo depth estimation network with adaptive depth range and depth interval

Song Zhang, Wenjia Xu, Zhiwei Wei +3

Multi-View Stereo~(MVS) is a fundamental problem in geometric computer vision which aims to reconstruct a scene using multi-view images with known camera parameters. However, the m…

cs.CV2023★ 2 cited

Linear building pattern recognition via spatial knowledge graph

Wei Zhiwei, Xiao Yi, Tong Ying +2

Building patterns are important urban structures that reflect the effect of the urban material and social-economic on a region. Previous researches are mostly based on the graph is…

cs.CV2023

Inferring High-level Geographical Concepts via Knowledge Graph and Multi-scale Data Integration: A Case Study of C-shaped Building Pattern Recognition

Zhiwei Wei, Yi Xiao, Wenjia Xu +4

Effective building pattern recognition is critical for understanding urban form, automating map generalization, and visualizing 3D city models. Most existing studies use object-ind…

cs.CV2022

Distinctive Image Captioning via CLIP Guided Group Optimization

Youyuan Zhang, Jiuniu Wang, Hao Wu +1

Image captioning models are usually trained according to human annotated ground-truth captions, which could generate accurate but generic captions. In this paper, we focus on gener…

cs.CV2022

Learning Prototype via Placeholder for Zero-shot Recognition

Zaiquan Yang, Yang Liu, Wenjia Xu +3

Zero-shot learning (ZSL) aims to recognize unseen classes by exploiting semantic descriptions shared between seen classes and unseen classes. Current methods show that it is effect…

cs.CV2022

Multi-dimension Geospatial feature learning for urban region function recognition

Wenjia Xu, Jiuniu Wang, Yirong Wu

Urban region function recognition plays a vital character in monitoring and managing the limited urban areas. Since urban functions are complex and full of social-economic properti…

cs.CV2022★ 32 cited

On Distinctive Image Captioning via Comparing and Reweighting

Jiuniu Wang, Wenjia Xu, Qingzhong Wang +1

Recent image captioning models are achieving impressive results based on popular metrics, i.e., BLEU, CIDEr, and SPICE. However, focusing on the most popular metrics that only cons…

cs.CV2022

Attribute Prototype Network for Any-Shot Learning

Wenjia Xu, Yongqin Xian, Jiuniu Wang +2

Any-shot image classification allows to recognize novel classes with only a few or even zero samples. For the task of zero-shot learning, visual attributes have been shown to play…

cs.CV2022★ 6 cited

VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learning

Wenjia Xu, Yongqin Xian, Jiuniu Wang +2

Human-annotated attributes serve as powerful semantic embeddings in zero-shot learning. However, their annotation process is labor-intensive and needs expert supervision. Current u…

cs.CV2021★ 14 cited

Human Attention in Fine-grained Classification

Yao Rong, Wenjia Xu, Zeynep Akata +1

The way humans attend to, process and classify a given image has the potential to vastly benefit the performance of deep learning models. Exploiting where humans are focusing can r…

cs.CV2021★ 1 cited

Group-based Distinctive Image Captioning with Memory Attention

Jiuniu Wang, Wenjia Xu, Qingzhong Wang +1

Describing images using natural language is widely known as image captioning, which has made consistent progress due to the development of computer vision and natural language gene…

cs.CV2020★ 18 cited

Where is the Model Looking At?--Concentrate and Explain the Network Attention

Wenjia Xu, Jiuniu Wang, Yang Wang +3

Image classification models have achieved satisfactory performance on many datasets, sometimes even better than human. However, The model attention is unclear since the lack of int…

cs.CV2020★ 8 cited

Attribute Prototype Network for Zero-Shot Learning

Wenjia Xu, Yongqin Xian, Jiuniu Wang +2

From the beginning of zero-shot learning research, visual attributes have been shown to play an important role. In order to better transfer attribute-based knowledge from known to…

cs.CV2020★ 2 cited

Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets

Jiuniu Wang, Wenjia Xu, Qingzhong Wang +1

A wide range of image captioning models has been developed, achieving significant improvement based on popular metrics, such as BLEU, CIDEr, and SPICE. However, although the genera…