Cross Modal Transformer: Towards Fast and Robust 3D Object Detection-Reference-Cited by-同舟云学术

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Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

Published:2023-10-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Yan Junjie¹,Liu Yingfei¹,Sun Jianjian¹,Jia Fan¹,Li Shuailin¹,Wang Tiancai¹,Zhang Xiangyu¹

Affiliation:

1. MEGVII Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377452.pdf?arnumber=10377452

Reference60 articles.

1. TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers

2. nuScenes: A Multimodal Dataset for Autonomous Driving

3. End-to-End Object Detection with Transformers

4. End-to-End Object Detection with Transformers

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Pedestrian Crossing Intention Prediction Based on Cross-Modal Transformer and Uncertainty-Aware Multi-Task Learning for Autonomous Driving;IEEE Transactions on Intelligent Transportation Systems;2024-09

2. A Systematic Survey of Transformer-Based 3D Object Detection for Autonomous Driving: Methods, Challenges and Trends;Drones;2024-08-22

3. Enhancing Intra- and Inter-Object Part Features for 3-D Object Detection Through LiDAR–Camera Fusion;IEEE Sensors Journal;2024-08-15

4. BAFusion: Bidirectional Attention Fusion for 3D Object Detection Based on LiDAR and Camera;Sensors;2024-07-20

5. IRBEVF-Q: Optimization of Image–Radar Fusion Algorithm Based on Bird’s Eye View Features;Sensors;2024-07-16

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