Xiao Lin

Positionsort ascending e-mail
PhD Candidate xiao.lin@upc.edu
Office Phone
D5-119 +34 934 011 066

Biography

Xiao received the degree in Software Engineering in 2010 and the M.Sc. in Research on Computer Vision in 2013, both from the South West Unviersity in China. He is currently doing his Ph.D. under the advisement of Josep Ramon Casas and Montse Pardas in the Image and Video Processing Group at UPC. He holds a scholarship from China Scholarship Council (CSC). His main research field is focused on 3D segmentation and human-object interaction analysis based on depth sensor.

Journal Articles top

2019
X. Lin, Sanchez-Escobedo, D., Casas, J., and Pardàs, M., “Depth Estimation and Semantic Segmentation from a Single RGB Image Using a Hybrid Convolutional Neural Network”, Sensors, vol. 19, no. 8, 2019. (4.75 MB)
2018
X. Lin, Casas, J., and Pardàs, M., “Temporally Coherent 3D Point Cloud Video Segmentation in Generic Scenes”, IEEE Transactions on Image Processing, vol. 27, no. 6, pp. 3087 - 3099, 2018. (24.37 MB)
2017
P. A. Martínez, Lin, X., Castelán, M., Casas, J., and Arechavaleta, G., “A closed-loop approach for tracking a humanoid robot using particle filtering and depth data”, Intelligent Service Robotics, vol. 10, no. 4, pp. 297–312, 2017. (88.92 KB)

Conference Papers top

2019
X. Lin, Casas, J., and Pardàs, M., “One Shot Learning for Generic Instance Segmentation in RGBD Videos”, in International Conference on Computer Vision, Theory and Applications, Prague, 2019. (1.64 MB)
2018
D. Sanchez-Escobedo, Lin, X., Casas, J., and Pardàs, M., “HybridNet for Depth Estimation and Semantic Segmentation”, in ICASSP 2018, Calgary, Alberta, Canada, 2018. (1.14 MB)
2017
X. Lin, Casas, J., and Pardàs, M., “3D Point Cloud Segmentation Using a Fully Connected Conditional Random Field”, in The 25th European Signal Processing Conference (EUSIPCO 2017), Kos island, Greece, 2017. (2.34 MB)
2016
X. Lin, Casas, J., and Pardàs, M., “Graph based Dynamic Segmentation of Generic Objects in 3D”, in CVPR SUNw: Scene Understanding Workshop, Las Vegas, US, 2016. (956.15 KB)
X. Lin, Casas, J., and Pardàs, M., “3D Point Cloud Segmentation Oriented to The Analysis of Interactions”, in The 24th European Signal Processing Conference (EUSIPCO 2016), Budapest, Hungary, 2016. (10.54 MB)
see all

Theses top

2018
X. Lin, “Semantic and Generic Object Segmentation for Scene Analysis Using RGB-D Data”, Universitat Politècnica de Catalunya (UPC), download link, 2018.

Projects top

MALEGRA - Multimodal Signal Processing and Machine Learning on Graphs National Jan
2017 		Jun
2021
BigGraph - Heterogeneous information and graph signal processing for the Big Data era. Application to high-throughput, remote sensing, multimedia and human computer interfaces. National Jan
2014 		Dec
2017
SGR14 - Image and Video Processing Group National Jan
2014 		Apr
2017

Demos and Resources top

Temporally Coherent 3D Point Cloud Video Segmentation in Generic Scenes Results Aug
2017
3D Point Cloud Segmentation using a Fully Connected Conditional Random Field Results Mar
2017
Interactive registration for 3D data fusion Demo Jul
2016
Graph based Dynamic Segmentation of Generic Objects in 3D Results May
2016
Human manipulation dataset Dataset Feb
2016