Search Results for author:
Found 10 papers, 3 papers with code
Lossless Point Cloud Attribute Compression with Normal-based Intra Prediction
In this paper, we propose a normal-based intra prediction scheme, which provides a more efficient lossless attribute compression by introducing the normals of point clouds.
RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network
In this paper, we propose a novel LiDAR point cloud frame interpolation method, which exploits range images (RIs) as an intermediate representation with CNNs to conduct the frame interpolation process.
An Unsupervised Optical Flow Estimation For LiDAR Image Sequences
Among these works, the optical flow estimation for LiDAR image sequences has become a key issue, especially for the motion estimation of the inter prediction in PCC.
BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values
There has been increasing interest in modeling survival data using deep learning methods in medical research.
Adverse event enrichment tests using VAERS
By appropriately addressing the issues of ties and excessive zeros in AE count data, our enrichment tests performed well as demonstrated by simulation studies and analyses of VAERS data.
Methodology
Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty
The experiment results show that the Dense2Sparse method obtained higher expected reward compared with the ones using standalone dense reward or sparse reward, and it also has a superior tolerance of system uncertainty.
DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values
There has been increasing interest in modelling survival data using deep learning methods in medical research.
COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis
There are substantial instructional videos on the Internet, which enables us to acquire knowledge for completing various tasks.
Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification
Furthermore, since different layers in a deep network capture feature maps of different scales, we use these feature maps to construct a spatial pyramid and then utilize multi-scale information to obtain more accurate attention scores, which are used to weight the local features in all spatial positions of feature maps to calculate attention maps.
Deep Hashing with Category Mask for Fast Video Retrieval
This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval.
