no code implementations • 27 May 2023 • Hui Li, Yongbiao Xiao, Chunyang Cheng, Zhongwei Shen, Xiaoning Song
Infrared and visible image fusion aims to generate synthetic images simultaneously containing salient features and rich texture details, which can be used to boost downstream tasks.
no code implementations • 27 May 2023 • Yongbiao Xiao, Hui Li, Chunyang Cheng, Xiaoning Song
Specifically, a local edge enhancement (LE2) module is proposed to improve the edge information under complex illumination conditions and preserve the essential features of image.
no code implementations • 16 Feb 2023 • Wenjie Zhang, Xiaoning Song, ZhenHua Feng, Tianyang Xu, XiaoJun Wu
Specifically, associating natural language words that fill the masked token with semantic relation labels (\textit{e. g.} \textit{``org:founded\_by}'') is difficult.
1 code implementation • 12 May 2022 • Shuang Wu, Xiaoning Song, ZhenHua Feng, Xiao-Jun Wu
To deal with this issue, we advocate a novel lexical enhancement method, InterFormer, that effectively reduces the amount of computational and memory costs by constructing non-flat lattices.
Ranked #9 on Chinese Named Entity Recognition on Resume NER
Chinese Named Entity Recognition named-entity-recognition +2
1 code implementation • 23 Jan 2022 • He-Feng Yin, Xiao-Jun Wu, Xiaoning Song
The second order image gradient orientations (SOIGO) can mitigate the adverse effect of noises in face images.
1 code implementation • ACL 2021 • Shuang Wu, Xiaoning Song, ZhenHua Feng
This paper presents a novel Multi-metadata Embedding based Cross-Transformer (MECT) to improve the performance of Chinese NER by fusing the structural information of Chinese characters.
no code implementations • 25 Jul 2020 • Jingqiao Zhao, Zhen-Hua Feng, Qiuqiang Kong, Xiaoning Song, Xiao-Jun Wu
This paper presents a Depthwise Disout Convolutional Neural Network (DD-CNN) for the detection and classification of urban acoustic scenes.
no code implementations • 1 Nov 2016 • Xiaoning Song, Zhen-Hua Feng, Guosheng Hu, Josef Kittler, William Christmas, Xiao-Jun Wu
The paper presents a dictionary integration algorithm using 3D morphable face models (3DMM) for pose-invariant collaborative-representation-based face classification.