1. token information raw_data에서 v1.0-trainval 폴더 안에 sample.json에서 token정보를 받아와서 저장. sample.json 예시 { "token": "fd8420396768425eabec9bdddf7e64b6", "timestamp": 1533201470448696, "prev": "", "next": "6eb8a3ff0abf4f3a9380a48f2a0b87ef", "scene_token": "e7ef871f77f44331aefdebc24ec034b7" } token_info/scene-0003.json 예시(token_info.py결과) ["fd8420396768425eabec9bdddf7e64b6", "6eb8a3ff0abf4f3a9380a48f2a0b..
https://arxiv.org/abs/1711.06396 VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality. To interface a highly sparse LiDAR point cloud with a region proposal network (RP arxiv.org 1. Point cloud의 '어떤 특성'때문에..
submission { "meta": { "use_camera": -- Whether this submission uses camera data as an input. "use_lidar": -- Whether this submission uses lidar data as an input. "use_radar": -- Whether this submission uses radar data as an input. "use_map": -- Whether this submission uses map data as an input. "use_external": -- Whether this submission uses external data as an input. }, "results": { sample_tok..
https://arxiv.org/abs/1612.00593 PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or collections of images. This, however, renders data unnecessarily voluminous and causes issues. In t arxiv.org Abstract point cloud는..
