Search Results for author: Zhen He

Found 22 papers, 5 papers with code

TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations

1 code implementation EMNLP 2021 Xianming Li, Xiaotian Luo, Chenghao Dong, Daichuan Yang, Beidi Luan, Zhen He

To address such a problem, this paper proposes a novel efficient entities and relations extraction model called TDEER, which stands for Translating Decoding Schema for Joint Extraction of Entities and Relations.

Joint Entity and Relation Extraction

Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition

no code implementations30 Jun 2022 Lin Yuan, Zhen He, Qiang Wang, Leiyang Xu, Xiang Ma

Human action recognition is a quite hugely investigated area where most remarkable action recognition networks usually use large-scale coarse-grained action datasets of daily human actions as inputs to state the superiority of their networks.

Action Recognition Transfer Learning

Automatic Generation of Product-Image Sequence in E-commerce

1 code implementation26 Jun 2022 Xiaochuan Fan, Chi Zhang, Yong Yang, Yue Shang, Xueying Zhang, Zhen He, Yun Xiao, Bo Long, Lingfei Wu

For a platform with billions of products, it is extremely time-costly and labor-expensive to manually pick and organize qualified images.

Scenario-based Multi-product Advertising Copywriting Generation for E-Commerce

no code implementations21 May 2022 Xueying Zhang, Kai Shen, Chi Zhang, Xiaochuan Fan, Yun Xiao, Zhen He, Bo Long, Lingfei Wu

In this paper, we proposed an automatic Scenario-based Multi-product Advertising Copywriting Generation system (SMPACG) for E-Commerce, which has been deployed on a leading Chinese e-commerce platform.

Language Modelling

Deep Graph Learning for Spatially-Varying Indoor Lighting Prediction

no code implementations13 Feb 2022 Jiayang Bai, Jie Guo, Chenchen Wan, Zhenyu Chen, Zhen He, Shan Yang, Piaopiao Yu, Yan Zhang, Yanwen Guo

At its core is a new lighting model (dubbed DSGLight) based on depth-augmented Spherical Gaussians (SG) and a Graph Convolutional Network (GCN) that infers the new lighting representation from a single LDR image of limited field-of-view.

Graph Learning

Automatic Product Copywriting for E-Commerce

no code implementations15 Dec 2021 Xueying Zhang, Yanyan Zou, Hainan Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Han Yu, Lingfei Wu

It consists of two main components: 1) natural language generation, which is built from a transformer-pointer network and a pre-trained sequence-to-sequence model based on millions of training data from our in-house platform; and 2) copywriting quality control, which is based on both automatic evaluation and human screening.

Product Recommendation Text Generation

Learning to Generate Visual Questions with Noisy Supervision

no code implementations NeurIPS 2021 Shen Kai, Lingfei Wu, Siliang Tang, Yueting Zhuang, Zhen He, Zhuoye Ding, Yun Xiao, Bo Long

The task of visual question generation (VQG) aims to generate human-like neural questions from an image and potentially other side information (e. g., answer type or the answer itself).

Question Generation

Semi-supervised learning for medical image classification using imbalanced training data

no code implementations20 Aug 2021 Tri Huynh, Aiden Nibali, Zhen He

Medical image classification is often challenging for two reasons: a lack of labelled examples due to expensive and time-consuming annotation protocols, and imbalanced class labels due to the relative scarcity of disease-positive individuals in the wider population.

Image Classification Medical Image Classification

Pose is all you need: The pose only group activity recognition system (POGARS)

no code implementations9 Aug 2021 Haritha Thilakarathne, Aiden Nibali, Zhen He, Stuart Morgan

We introduce a novel deep learning based group activity recognition approach called the Pose Only Group Activity Recognition System (POGARS), designed to use only tracked poses of people to predict the performed group activity.

Action Classification Group Activity Recognition +1

Adaptive Smooth Disturbance Observer-Based Fast Finite-Time Attitude Tracking Control of a Small Unmanned Helicopter

no code implementations26 Jun 2021 Xidong Wang, Zhan Li, Xinghu Yu, Zhen He

In this paper, a novel adaptive smooth disturbance observer-based fast finite-time adaptive backstepping control scheme is presented for the attitude tracking of the 3-DOF helicopter system subject to compound disturbances.

A comprehensive solution to retrieval-based chatbot construction

no code implementations11 Jun 2021 Kristen Moore, Shenjun Zhong, Zhen He, Torsten Rudolf, Nils Fisher, Brandon Victor, Neha Jindal

In this paper we present the results of our experiments in training and deploying a self-supervised retrieval-based chatbot trained with contrastive learning for assisting customer support agents.

Chatbot Contrastive Learning +1

Enhancing Trajectory Prediction using Sparse Outputs: Application to Team Sports

no code implementations1 Jun 2021 Brandon Victor, Aiden Nibali, Zhen He, David L. Carey

Sophisticated trajectory prediction models that effectively mimic team dynamics have many potential uses for sports coaches, broadcasters and spectators.

Trajectory Prediction

Adaptive Fast Smooth Second-Order Sliding Mode Control for Attitude Tracking of a 3-DOF Helicopter

no code implementations25 Aug 2020 Xidong Wang, Zhan Li, Zhen He, Huijun Gao

This paper presents a novel adaptive fast smooth second-order sliding mode control for the attitude tracking of the three degree-of-freedom (3-DOF) helicopter system with lumped disturbances.

Systems and Control Systems and Control

Distributed Training of Deep Learning Models: A Taxonomic Perspective

no code implementations8 Jul 2020 Matthias Langer, Zhen He, Wenny Rahayu, Yanbo Xue

Distributed deep learning systems (DDLS) train deep neural network models by utilizing the distributed resources of a cluster.

Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

1 code implementation CVPR 2019 Zhen He, Jian Li, Daxue Liu, Hangen He, David Barber

To achieve both label-free and end-to-end learning of MOT, we propose a Tracking-by-Animation framework, where a differentiable neural model first tracks objects from input frames and then animates these objects into reconstructed frames.

Multi-Object Tracking Online Multi-Object Tracking

3D Human Pose Estimation with 2D Marginal Heatmaps

1 code implementation5 Jun 2018 Aiden Nibali, Zhen He, Stuart Morgan, Luke Prendergast

Automatically determining three-dimensional human pose from monocular RGB image data is a challenging problem.

3D Human Pose Estimation

Numerical Coordinate Regression with Convolutional Neural Networks

2 code implementations23 Jan 2018 Aiden Nibali, Zhen He, Stuart Morgan, Luke Prendergast

We study deep learning approaches to inferring numerical coordinates for points of interest in an input image.

Pose Estimation

Continuous Video to Simple Signals for Swimming Stroke Detection with Convolutional Neural Networks

no code implementations28 May 2017 Brandon Victor, Zhen He, Stuart Morgan, Dino Miniutti

Most research has been focused on action recognition and using it to classify many clips in continuous video for action localisation.

Action Recognition

Extraction and Classification of Diving Clips from Continuous Video Footage

no code implementations25 May 2017 Aiden Nibali, Zhen He, Stuart Morgan, Daniel Greenwood

Due to recent advances in technology, the recording and analysis of video data has become an increasingly common component of athlete training programmes.

Classification General Classification

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