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Point Transformer V3 Extreme: 1st Place Solution for 2024 Waymo Open Dataset Challenge in Semantic Segmentation

Authors :
Wu, Xiaoyang
Xu, Xiang
Kong, Lingdong
Pan, Liang
Liu, Ziwei
He, Tong
Ouyang, Wanli
Zhao, Hengshuang
Publication Year :
2024

Abstract

In this technical report, we detail our first-place solution for the 2024 Waymo Open Dataset Challenge's semantic segmentation track. We significantly enhanced the performance of Point Transformer V3 on the Waymo benchmark by implementing cutting-edge, plug-and-play training and inference technologies. Notably, our advanced version, Point Transformer V3 Extreme, leverages multi-frame training and a no-clipping-point policy, achieving substantial gains over the original PTv3 performance. Additionally, employing a straightforward model ensemble strategy further boosted our results. This approach secured us the top position on the Waymo Open Dataset semantic segmentation leaderboard, markedly outperforming other entries.<br />Comment: 1st Place Solution for 2024 Waymo Open Dataset Challenge in Semantic Segmentation

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2407.15282
Document Type :
Working Paper