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20182026
most citedASTRAL: Adversarial Trained LSTM-CNN for Named Entity Recognition

73 citations · 287 across the 22 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

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

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…