no code implementations • EMNLP 2020 • Rui Cai, Mirella Lapata
Cross-lingual semantic role labeling (SRL) aims at leveraging resources in a source language to minimize the effort required to construct annotations or models for a new target language.
no code implementations • 9 Apr 2024 • Rui Cai, Shichao Pei, Xiangliang Zhang
Relational learning is an essential task in the domain of knowledge representation, particularly in knowledge graph completion (KGC). While relational learning in traditional single-modal settings has been extensively studied, exploring it within a multimodal KGC context presents distinct challenges and opportunities.
3 code implementations • 13 Nov 2023 • Rui Cai, Xuying Ning, Peter N. Belhumeur
In the post-pandemic era, wearing face masks has posed great challenge to the ordinary face recognition.
1 code implementation • 26 Aug 2022 • Yabing Wang, Jianfeng Dong, Tianxiang Liang, Minsong Zhang, Rui Cai, Xun Wang
In this paper, we propose a noise-robust cross-lingual cross-modal retrieval method for low-resource languages.
no code implementations • IJCNLP 2019 • Rui Cai, Mirella Lapata
The successful application of neural networks to a variety of NLP tasks has provided strong impetus to develop end-to-end models for semantic role labeling which forego the need for extensive feature engineering.
1 code implementation • TACL 2019 • Rui Cai, Mirella Lapata
In this paper we focus on learning dependency aware representations for semantic role labeling without recourse to an external parser.
no code implementations • CVPR 2017 • Yanhua Cheng, Rui Cai, Zhiwei Li, Xin Zhao, Kaiqi Huang
This layer can learn to adjust the contributions of RGB and depth over each pixel for high-performance object recognition.
Ranked #79 on Semantic Segmentation on NYU Depth v2
no code implementations • CVPR 2016 • Chi Zhang, Zhiwei Li, Rui Cai, Hongyang Chao, Yong Rui
In this paper, we propose an RGB-D camera localization approach which takes an effective geometry constraint, i. e. silhouette consistency, into consideration.
no code implementations • ICCV 2015 • Yanhua Cheng, Rui Cai, Chi Zhang, Zhiwei Li, Xin Zhao, Kaiqi Huang, Yong Rui
The reasons are in two-fold: (1) existing similarity measures are sensitive to object pose and scale changes, as well as intra-class variations; and (2) effectively fusing RGB and depth cues is still an open problem.
no code implementations • ICCV 2015 • Chi Zhang, Zhiwei Li, Yanhua Cheng, Rui Cai, Hongyang Chao, Yong Rui
We present a novel global stereo model designed for view interpolation.
no code implementations • CVPR 2013 • Qiang Hao, Rui Cai, Zhiwei Li, Lei Zhang, Yanwei Pang, Feng Wu, Yong Rui
3D model-based object recognition has been a noticeable research trend in recent years.