57 citations · 449 across the 18 of their papers we have counts for
18 papers
CT-Net: Arbitrary-Shaped Text Detection via Contour Transformer
Zhiwen Shao, Yuchen Su, Yong Zhou +4
Contour based scene text detection methods have rapidly developed recently, but still suffer from inaccurate frontend contour initialization, multi-stage error accumulation, or def…
Towards Commonsense Knowledge based Fuzzy Systems for Supporting Size-Related Fine-Grained Object Detection
Pu Zhang, Tianhua Chen, Bin Liu
Deep learning has become the dominating approach for object detection. To achieve accurate fine-grained detection, one needs to employ a large enough model and a vast amount of dat…
Motion Robust High-Speed Light-Weighted Object Detection With Event Camera
Bingde Liu, Chang Xu, Wen Yang +2
In this work, we propose a motion robust and high-speed detection pipeline which better leverages the event data. First, we design an event stream representation called temporal ac…
TextDCT: Arbitrary-Shaped Text Detection via Discrete Cosine Transform Mask
Yuchen Su, Zhiwen Shao, Yong Zhou +4
Arbitrary-shaped scene text detection is a challenging task due to the variety of text changes in font, size, color, and orientation. Most existing regression based methods resort…
Lifelong Domain Word Embedding via Meta-Learning
Hu Xu, Bing Liu, Lei Shu +1
Learning high-quality domain word embeddings is important for achieving good performance in many NLP tasks. General-purpose embeddings trained on large-scale corpora are often sub-…
Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction
Hu Xu, Bing Liu, Lei Shu +1
One key task of fine-grained sentiment analysis of product reviews is to extract product aspects or features that users have expressed opinions on. This paper focuses on supervised…