no code implementations • 18 Oct 2022 • Xuan Yang, Quanjin Tao, Xiao Feng, Donghong Cai, Xiang Ren, Yang Yang
In this paper, we propose MMGA (Multimodal learning with Graph Alignment), a novel multimodal pre-training framework to incorporate information from graph (social network), image and text modalities on social media to enhance user representation learning.
no code implementations • ACL 2021 • Lemao Liu, Haisong Zhang, Haiyun Jiang, Yangming Li, Enbo Zhao, Kun Xu, Linfeng Song, Suncong Zheng, Botong Zhou, Dick Zhu, Xiao Feng, Tao Chen, Tao Yang, Dong Yu, Feng Zhang, Zhanhui Kang, Shuming Shi
This paper introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
no code implementations • 26 Jan 2021 • Andrea Cavagna, Xiao Feng, Stefania Melillo, Leonardo Parisi, Lorena Postiglione, Pablo Villegas
With the rotation of the cameras we overcome the limitations of standard static systems that restrict the duration of the collected data to the short interval of time in which targets are in the cameras common field of view, but at the same time we change in time the external parameters of the system, which have then to be calibrated frame-by-frame.
no code implementations • 14 Jan 2021 • Riccardo Beschi, Xiao Feng, Stefania Melillo, Leonardo Parisi, Lorena Postiglione
The reconstruction of a scene via a stereo-camera system is a two-steps process, where at first images from different cameras are matched to identify the set of point-to-point correspondences that then will actually be reconstructed in the three dimensional real world.
no code implementations • 31 Dec 2020 • Haisong Zhang, Lemao Liu, Haiyun Jiang, Yangming Li, Enbo Zhao, Kun Xu, Linfeng Song, Suncong Zheng, Botong Zhou, Jianchen Zhu, Xiao Feng, Tao Chen, Tao Yang, Dong Yu, Feng Zhang, Zhanhui Kang, Shuming Shi
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.
no code implementations • 30 Jun 2020 • Xinyan Zhao, Xiao Feng, Haoming Zhong, Jun Yao, Huanhuan Chen
CAR-Transformer (1) revises each condition value based on the whole conversation and original conditions values, and (2) it encodes the revised conditions and utilizes the conditions embedding to select an answer.