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ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention (ECCV 2024)

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ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention

This repo is the official implementation of paper: ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention. It achieves 73.8 mAP L2 on Waymo Open Dataset val and 72.4 NDS on NuScenes val. The scatterformer achieve real-time speed of 23 FPS.

News

  • [24-06-21] Scatterformer is accepted by ECCV 2024!
  • [24-07-18] Training code released

Main results

Waymo Open Dataset validation

Model #Sweeps mAP/H_L1 mAP/H_L2 Veh_L1 Veh_L2 Ped_L1 Ped_L2 Cyc_L1 Cyc_L2 Log
ScatterFormer (100%) 1 81.8/79.7 75.7/73.8 81.0/80.5 73.1/72.7 84.5/79.9 77.0/72.6 79.9/78.9 77.1/76.1 Log
ScatterFormer (20%) 1 80.3/78.0 74.1/72.0 79.6/79.1 71.6/71.2 83.5/78.3 75.9/71.0 77.7/76.6 74.8/73.7 Log

NuScenes validation

Model mAP NDS mATE mASE mAOE mAVE mAAE ckpt Log
ScatterFormer 68.3 72.4 26.5 24.5 24.7 23.3 18.8 ckpt Log

Usage

Installation

Please refer to INSTALL.md for installation.

Dataset Preparation

Please follow the instructions from OpenPCDet. We adopt the same data generation process.

Sparse Group-wise Convolution

ScatterFormer relies on a group-wise sparse convolution, please find this hacked version of spconv

Training

# multi-gpu training
cd tools
bash scripts/dist_train.sh 8 --cfg_file <CONFIG_FILE> [other optional arguments]

Testing

# multi-gpu testing
cd tools
bash scripts/dist_test.sh 8 --cfg_file <CONFIG_FILE> --ckpt <CHECKPOINT_FILE>

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ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention (ECCV 2024)

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