تقرير
Point Transformer V3 Extreme: 1st Place Solution for 2024 Waymo Open Dataset Challenge in Semantic Segmentation
| العنوان: | Point Transformer V3 Extreme: 1st Place Solution for 2024 Waymo Open Dataset Challenge in Semantic Segmentation |
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| المؤلفون: | Wu, Xiaoyang, Xu, Xiang, Kong, Lingdong, Pan, Liang, Liu, Ziwei, He, Tong, Ouyang, Wanli, Zhao, Hengshuang |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | 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. Comment: 1st Place Solution for 2024 Waymo Open Dataset Challenge in Semantic Segmentation |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.15282 |
| رقم الأكسشن: | edsarx.2407.15282 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |