3.4 Masked-Modal Training for Robustness 四、实验结果 论文链接:Cross Modal Transformer: Towards Fast and Robust 3D Object Detection 代码链接:github.com/junjie18/CMT 作者:Junjie Yan, Yingfei Liu, Jianjian Sun, Fan Jia, Shuailin Li, Tiancai Wang, Xiangyu Zhang 发表单位:旷视科技 会议/期刊:ICCV...
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection. ICCV, 2023. 论文地址 代码地址 目录 主要内容 研究背景 方法 坐标编码模块(CEM) Position-guided Query Generator Decoder和Loss Masked-Modal Training 实验 总结与讨论 1 主要内容 本文拟提出了一种鲁棒的多模态3D目标检测器Cross Modal ...
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection ICCV 2023 在本文中,我们提出了 Cross-Modal Transformer (CMT),这是一种简单而有效的端到端管道,用于鲁棒的 3D 对象检测(见图 1(c))。首先,我们提出了坐标编码模块(CEM),它通过将 3D 点集隐式编码为多模态标记来生成位置感知特征。具体...
操作简化：无需复杂的2D到3D转换，CMT仅通过基础操作就能达到当前的性能顶峰，表现出极高的效率和鲁棒性。多模态适应：即使没有激光雷达，CMT也能与视觉方法相当，展现其在不同条件下的适应性。论文中，作者对比了多模态3D目标检测的不同方法，如BEVFusion、Transfusion和CMT，后者通过Transformer架构实现图...
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection Junjie Yan Yingfei Liu ✉ Jianjian Sun Fan Jia Tiancai Wang Xiangyu Zhang MEGVII Technology Shuailin Li Abstract In this paper, we propose a robust 3D detector, named Cross Modal Transformer (...
摘要: Transformers have been recognized as powerful tools for various cross-modal tasks due to their superior ability to perform representation learning through self-attention. Existing transformer-based...关键词: Cross-modal learning Representation learning Similarity learning Metric learning ...
@article{yan2023cross,title={Cross Modal Transformer via Coordinates Encoding for 3D Object Dectection},author={Yan, Junjie and Liu, Yingfei and Sun, Jianjian and Jia, Fan and Li, Shuailin and Wang, Tiancai and Zhang, Xiangyu},journal={arXiv preprint arXiv:2301.01283},year={2023}} ...
[ICCV 2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection - Woogie-Boogie/CMT
To this end, we design an innovative Transformer-based Adaptive Cross-modal Fusion Network (TACFN). Specifically, for the redundant features, we make one modality perform intra-modal feature selection through a self-attention mechanism, so that the selected features can adaptively and efficiently ...