#Waymo

Discover EFG, an adaptable deep learning framework offering capabilities for 3D object detection and tracking, suitable for diverse research applications with structured project templates. This framework supports advanced features, including COCO Panoptic Segmentation and Pytorch 2.0 compatibility. Recent code releases for ICCV2023 and CVPR2023 papers integrate methodologies like TrajectoryFormer and ConQueR. Optimized for extensive datasets such as Waymo and nuScenes, EFG achieves notable benchmark performances on NVIDIA A100 GPUs. It provides a versatile solution for researchers aiming for flexibility and efficiency in a progressive deep learning landscape.

The Dynamic Sparse Voxel Transformer (DSVT) efficiently analyzes large-scale point clouds in autonomous driving. Excelling with state-of-the-art performance in the Waymo Open Dataset, it achieves real-time 3D object detection through unique rotated set partitioning. With minimal dependencies, DSVT optimizes performance in both single-sweep and multi-sweep configurations. Highlighted at CVPR2023 and integrated into the OpenPCDet framework, DSVT represents significant advancements in 3D perception without overstating its capabilities.