Rangeinet: Fast Lidar Point Cloud Temporal Interpolation
Author:
Affiliation:
1. University of Electronic Science and Technology of China,Chengdu,China
2. Nanyang Technological University,Singapore
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747825.pdf?arnumber=9747825
Reference20 articles.
1. SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation
2. Are we ready for autonomous driving? The KITTI vision benchmark suite
3. nuScenes: A Multimodal Dataset for Autonomous Driving
4. U-net: Convolutional networks for biomedical image segmentation;ronneberger;Proc Int Conf Med Image Comput Comput -Assist Intervent (MICCAI),2015
5. FLAVR: Flow-agnostic video representations for fast frame interpolation;kalluri;arXiv preprint arXiv 0904 2012,2021
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3. Learning Spatial-Temporal Embeddings for Sequential Point Cloud Frame Interpolation;2023 IEEE International Conference on Image Processing (ICIP);2023-10-08
4. Spatial-Temporal Consistency Refinement Network for Dynamic Point Cloud Frame Interpolation;2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW);2023-07
5. BIRD-PCC: Bi-Directional Range Image-Based Deep Lidar Point Cloud Compression;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04
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