| Pub. | Author | Title | Links |
|---|---|---|---|
| DCC 2020 | NJU | Multiscale Point Cloud Geometry Compression | Paper/Code |
| TCSVT 2021 | NJU | Lossy Point Cloud Geometry Compression via End-to-End Learning [Learned Point Cloud Geometry Compression in arxiv 2019] | Paper |
| ACM MM 2019 | ZJU | 3D Point Cloud Geometry Compression on Deep Learning | Paper |
| CVPR 2020 | Uber | OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression | Paper |
| ICME 2020 | SZU | Lossy Geometry Compression Of 3d Point Cloud Data Via An Adaptive Octree-Guided Network | Paper/Code |
| ICIP 2019 | L2S | Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression | Paper/Code |
| ICMEW 2020 | IST | Deep Learning-Based Point Cloud Geometry Coding: RD Control Through Implicit and Explicit Quantization | Paper |
| JSTSP 2021 | IST | Adaptive Deep Learning-based Point Cloud Geometry Coding | Paper |
| MMSP 2020 | CNRS | Improved Deep Point Cloud Geometry Compression | paper/Code |
| ICRA 2019 | Nagoya University | Point Cloud Compression for 3D LiDAR Sensor using Recurrent Neural Network with Residual Blocks | Paper/Code |
| IEEE ROBOTICS AND AUTOMATION LETTERS 2019 | HKUST | A novel point cloud compression algorithm based on clustering | Paper |
| Pub. | Author | Title | Links |
|---|---|---|---|
| ACM MM 2020 | SZU | An Advanced LiDAR Point Cloud Sequence Coding Scheme for Autonomous Driving | Paper |
| IEEE ACCESS 2019 | Nagoya University | Real-time Streaming Point Cloud Compression for 3D LiDAR Sensor Using U-net | Paper |
| IEEE ROBOTICS AND AUTOMATION LETTERS 2020 | HKU | A Novel Coding Architecture for LiDAR Point Cloud Sequence | Paper |