Dynamic Point Cloud Interpolation-Reference-Cited by-同舟云学术

Dynamic Point Cloud Interpolation

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Akhtar Anique¹,Li Zhu¹,Van der Auwera Geert²,Chen Jianle²

Affiliation:

1. University of Missouri-Kansas City

2. Qualcomm Technologies Inc

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747105.pdf?arnumber=9747105

Reference19 articles.

1. FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation

2. HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-Scale Point Clouds

3. PointPWC-Net: A Coarse-to-Fine Network for Supervised and Self-Supervised Scene Flow Estimation on 3D Point Clouds;wu;arXiv preprint arXiv 1911 12945,2019

4. Just Go With the Flow: Self-Supervised Scene Flow Estimation

5. PointINet: Point Cloud Frame Interpolation Network;lu;2012 arXiv preprint arXiv,2020

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1. Improved Video-Based Point Cloud Compression via Segmentation;Sensors;2024-07-01

2. Improved Patch Packing and Refining Segmentation for the V-PCC Standard;Applied Sciences;2024-02-08

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. A Dynamic 3D Point Cloud Dataset for Immersive Applications;Proceedings of the 14th Conference on ACM Multimedia Systems;2023-06-07