activity
20192024
most citedShallow Feature Based Dense Attention Network for Crowd Counting

24 citations · 42 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL20223 cited

InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddings

Xing Wu, Chaochen Gao, Zijia Lin +3

Contrastive learning has been extensively studied in sentence embedding learning, which assumes that the embeddings of different views of the same sentence are closer. The constrai…

cs.CV2022

RaP: Redundancy-aware Video-language Pre-training for Text-Video Retrieval

Xing Wu, Chaochen Gao, Zijia Lin +3

Video language pre-training methods have mainly adopted sparse sampling techniques to alleviate the temporal redundancy of videos. Though effective, sparse sampling still suffers i…

cs.CL20205 cited

UniTrans: Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled Data

Qianhui Wu, Zijia Lin, Börje F. Karlsson +2

Prior works in cross-lingual named entity recognition (NER) with no/little labeled data fall into two primary categories: model transfer based and data transfer based methods. In t…

cs.CV202024 cited

Shallow Feature Based Dense Attention Network for Crowd Counting

Yunqi Miao, Zijia Lin, Guiguang Ding +1

While the performance of crowd counting via deep learning has been improved dramatically in the recent years, it remains an ingrained problem due to cluttered backgrounds and varyi…

cs.CL2020

Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language

Qianhui Wu, Zijia Lin, Börje F. Karlsson +2

To better tackle the named entity recognition (NER) problem on languages with little/no labeled data, cross-lingual NER must effectively leverage knowledge learned from source lang…

cs.CV2020

IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval

Hui Chen, Guiguang Ding, Xudong Liu +3

Enabling bi-directional retrieval of images and texts is important for understanding the correspondence between vision and language. Existing methods leverage the attention mechani…