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Found 7 papers, 3 papers with code
Noise-robust Cross-modal Interactive Learning with Text2Image Mask for Multi-modal Neural Machine Translation
This paper proposes a noise-robust multi-modal interactive fusion approach with cross-modal relation-aware mask mechanism for MNMT.
基于图文细粒度对齐语义引导的多模态神经机器翻译方法(Based on Semantic Guidance of Fine-grained Alignment of Image-Text for Multi-modal Neural Machine Translation)
“多模态神经机器翻译旨在利用视觉信息来提高文本翻译质量。传统多模态机器翻译将图像的全局语义信息融入到翻译模型, 而忽略了图像的细粒度信息对翻译质量的影响。对此, 该文提出一种基于图文细粒度对齐语义引导的多模态神经机器翻译方法, 该方法首先跨模态交互图文信息, 以提取图文细粒度对齐语义信息, 然后以图文细粒度对齐语义信息为枢纽, 采用门控机制将多模态细粒度信息对齐到文本信息上, 实现图文多模态特征融合。在多模态机器翻译基准数据集Multi30K 英语→德语、英语→法语以及英语→捷克语翻译任务上的实验结果表明, 论文提出方法的有效性, 并且优于大多数最先进的多模态机器翻译方法。”
SYENet: A Simple Yet Effective Network for Multiple Low-Level Vision Tasks with Real-time Performance on Mobile Device
To effectively connect the results by asymmetrical branches, a Quadratic Connection Unit(QCU) is proposed.
High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios
First, an absolute code phase is predicted from base station information, and integrated solution of the INS DR and real-time kinematic (RTK) results through an extended Kalman filter (EKF).
Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report
The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing.
Design of Automatic Driving Safety Level and Positioning Accuracy
Autonomous driving is a hot research topic in the frontier of science and technology.
Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation
We introduce an explorative active learning (AL) algorithm based on Gaussian process regression and marginalized graph kernel (GPR-MGK) to explore chemical space with minimum cost.
