Picture for Lili Zhao

Lili Zhao

Lossless Point Cloud Attribute Compression with Normal-based Intra Prediction

Jun 23, 2021
Qian Yin, Qingshan Ren, Lili Zhao, Wenyi Wang, Jianwen Chen

Figure 1 for Lossless Point Cloud Attribute Compression with Normal-based Intra Prediction

Figure 2 for Lossless Point Cloud Attribute Compression with Normal-based Intra Prediction

Figure 3 for Lossless Point Cloud Attribute Compression with Normal-based Intra Prediction

Figure 4 for Lossless Point Cloud Attribute Compression with Normal-based Intra Prediction

* Accepted by the IEEE International Symposium on Broadband Multimedia Systems and Broadcasting 2021

Access Paper or Ask Questions

RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network

Jun 01, 2021
Lili Zhao, Zezhi Zhu, Xuhu Lin, Xuezhou Guo, Qian Yin, Wenyi Wang, Jianwen Chen

Figure 1 for RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network

Figure 2 for RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network

Figure 3 for RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network

Figure 4 for RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network

* Accepted by the IEEE International Symposium on Broadband Multimedia Systems and Broadcasting 2021

Access Paper or Ask Questions

An Unsupervised Optical Flow Estimation For LiDAR Image Sequences

May 28, 2021
Xuezhou Guo, Xuhu Lin, Lili Zhao, Zezhi Zhu, Jianwen Chen

Figure 1 for An Unsupervised Optical Flow Estimation For LiDAR Image Sequences

Figure 2 for An Unsupervised Optical Flow Estimation For LiDAR Image Sequences

Figure 3 for An Unsupervised Optical Flow Estimation For LiDAR Image Sequences

Figure 4 for An Unsupervised Optical Flow Estimation For LiDAR Image Sequences

* Accepted by ICIP2021

Access Paper or Ask Questions

BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values

Jan 07, 2021
Dai Feng, Lili Zhao

Figure 1 for BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values

Figure 2 for BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values

Figure 3 for BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values

Figure 4 for BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values

Access Paper or Ask Questions

DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

Aug 06, 2019
Lili Zhao, Dai Feng

Figure 1 for DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

Figure 2 for DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

Figure 3 for DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

Figure 4 for DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

* 12 pages, 4 figures

Access Paper or Ask Questions

COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

Mar 07, 2019
Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, Jie Zhou

Figure 1 for COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

Figure 2 for COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

Figure 3 for COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

Figure 4 for COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

* CVPR2019, project page: https://coin-dataset.github.io/

Access Paper or Ask Questions

Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Aug 03, 2018
Yang Du, Chunfeng Yuan, Bing Li, Lili Zhao, Yangxi Li, Weiming Hu

Figure 1 for Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Figure 2 for Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Figure 3 for Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Figure 4 for Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

* Accepted by ECCV2018

Access Paper or Ask Questions