Awesome-3D-Object-Detection

Why we included this project

Anyone starting out in LiDAR-based 3D object detection, the perception task behind most autonomous driving stacks, will get a clear map of the field from this list. It organizes the research into datasets, the main conferences and workshops, and method categories, so you can follow the progression from early point-cloud work to recent CVPR and Waymo challenge entries. The dataset section alone is worth a look when planning experiments: it lists KITTI, nuScenes, Lyft, and Waymo with their sample counts, which saves a lot of digging. Teams scoping a perception project can also use it to spot which methods ship code and which benchmarks are realistic targets. It is a curated index rather than runnable software, which is what you want when the goal is literature review and baseline selection.