no code implementations • EMNLP 2021 • Raphael Tang, Karun Kumar, Kendra Chalkley, Ji Xin, Liming Zhang, Wenyan Li, Gefei Yang, Yajie Mao, Junho Shin, Geoffrey Craig Murray, Jimmy Lin
Query auto completion (QAC) is the task of predicting a search engine user’s final query from their intermediate, incomplete query.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
1 code implementation • 20 Nov 2023 • Xin Zhang, Yingze Song, Tingting Song, Degang Yang, Yichen Ye, Jie zhou, Liming Zhang
In response to the above questions, the Alterable Kernel Convolution (AKConv) is explored in this work, which gives the convolution kernel an arbitrary number of parameters and arbitrary sampled shapes to provide richer options for the trade-off between network overhead and performance.
no code implementations • 21 Sep 2023 • Qingtian Wu, Liming Zhang
Extreme head postures pose a common challenge across a spectrum of facial analysis tasks, including face detection, facial landmark detection (FLD), and head pose estimation (HPE).
no code implementations • 28 Jan 2023 • Luyu Jiang, Dantong Ouyang, Qi Zhang, Liming Zhang
Local search is an effective method for solving large-scale combinatorial optimization problems, and it has made remarkable progress in recent years through several subtle mechanisms.
no code implementations • 30 Aug 2021 • Bo Zhang, Tao Chen, Bin Wang, Xiaofeng Wu, Liming Zhang, Jiayuan Fan
Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled data.
no code implementations • 14 Jul 2021 • Tao Qian, Lei Dai, Liming Zhang, Zehua Chen
With straightforward mathematical formulation applicable to both univariate and multivariate objective functions, the global minimum value and all the global minimizers are located through two decreasing sequences of compact sets in, respectively, the domain and range spaces.
1 code implementation • 14 Oct 2020 • Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao
Extending existing deep generative models from static to dynamic graphs is a challenging task, which requires to handle the factorization of static and dynamic characteristics as well as mutual interactions among node and edge patterns.
no code implementations • 20 Sep 2020 • Liming Zhang, Liang Zhao, Dieter Pfoser
Inspired by the success of deep generative neural networks for images and texts, a fast-developing research topic is deep generative models for trajectory data which can learn expressively explanatory models for sophisticated latent patterns.
1 code implementation • 17 May 2020 • Liming Zhang, Liang Zhao, Shan Qin, Dieter Pfoser
The recent deep generative models for static graphs that are now being actively developed have achieved significant success in areas such as molecule design.
no code implementations • 27 Apr 2020 • Liming Zhang, Andreas Züfle, Dieter Pfoser
Urban areas provide us with a treasure trove of available data capturing almost every aspect of a population's life.
no code implementations • 15 Apr 2020 • Liming Zhang
On the other side, we consider such Co-HAR as a dense labelling problem that classify each sample on a time step with a label to provide high-fidelity and duration-varied support to applications.
no code implementations • 27 Jan 2020 • Qiwei Xie, Qian Long, Liming Zhang, Zhao Sun
The system is a real-time multi-scheme integrated innovation system, which combines stereo matching algorithm with machine learning based obstacle detection approach and takes advantage of the distributed computing technology of a mobile platform with GPU and CPUs.
no code implementations • 17 Mar 2018 • Chunyu Tan, Liming Zhang, Hau-Tieng Wu
The proposed compression algorithm is applied to the electrocardiogram signal.
no code implementations • CVPR 2016 • Guibo Luo, Yuesheng Zhu, Zhaotian Li, Liming Zhang
However, in the synthesis process, the background occluded by the foreground objects might be exposed in the new view, resulting in some holes in the synthetized video.