Search Results for author: Feng Xiao

Found 7 papers, 0 papers with code

StyleDyRF: Zero-shot 4D Style Transfer for Dynamic Neural Radiance Fields

no code implementations13 Mar 2024 Hongbin Xu, Weitao Chen, Feng Xiao, Baigui Sun, Wenxiong Kang

In this paper, we introduce StyleDyRF, a method that represents the 4D feature space by deforming a canonical feature volume and learns a linear style transformation matrix on the feature volume in a data-driven fashion.

Style Transfer

SeCG: Semantic-Enhanced 3D Visual Grounding via Cross-modal Graph Attention

no code implementations13 Mar 2024 Feng Xiao, Hongbin Xu, Qiuxia Wu, Wenxiong Kang

3D visual grounding aims to automatically locate the 3D region of the specified object given the corresponding textual description.

Graph Attention Relation +2

Restricted Generative Projection for One-Class Classification and Anomaly Detection

no code implementations9 Jul 2023 Feng Xiao, Ruoyu Sun, Jicong Fan

The core idea is to learn a mapping to transform the unknown distribution of training (normal) data to a known target distribution.

Informativeness One-Class Classification

Demand Forecasting in Bike-sharing Systems Based on A Multiple Spatiotemporal Fusion Network

no code implementations23 Sep 2020 Xiao Yan, Gang Kou, Feng Xiao, Dapeng Zhang, Xianghua Gan

Spatial and temporal features are critical for demand forecasting in BSSs, but it is challenging to extract spatiotemporal dynamics.

Ensemble Learning Feature Importance

ICSTrace: A Malicious IP Traceback Model for Attacking Data of Industrial Control System

no code implementations30 Dec 2019 Feng Xiao, Qiang Xu

Considering the attacks against industrial control system are mostly organized and premeditated actions, IP traceback is significant for the security of industrial control system.

Clustering

Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network

no code implementations15 Apr 2019 Feng Xiao, Dapeng Zhang, Gang Kou, Lu Li

To collectively forecast the demand for ride-sourcing services in all regions of a city, the deep learning approaches have been applied with commendable results.

A Deep Learning Model for Traffic Flow State Classification Based on Smart Phone Sensor Data

no code implementations26 Sep 2017 Wenwen Tu, Feng Xiao, Liping Fu, Guangyuan Pan

A total of 747, 856 sets of data are generated and used for both traffic flow states classification and sensitivity analysis of input variables.

Classification Computational Efficiency +1

Cannot find the paper you are looking for? You can Submit a new open access paper.