Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition-Reference-Cited by-同舟云学术

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Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition

Published:2023-10-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Tziafas Georgios¹,Kasaei Hamidreza¹

Affiliation:

1. University of Groningen,Department of Artificial Intelligence,The Netherlands

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10341341/10341342/10341422.pdf?arnumber=10341422

Reference48 articles.

1. A Multi-Modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling

2. A Multi-Modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling

3. BEiT: BERT Pre-Training of Image Transformers;Bao;CoRR,2021

4. Depth kernel descriptors for object recognition

5. Exploiting Multi-layer Features Using a CNN-RNN Approach for RGB-D Object Recognition

Cited by 3 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. CPROS: A Multimodal Decision-Level Fusion Detection Method Based on Category Probability Sets;Remote Sensing;2024-07-27

2. ForceSight: Text-Guided Mobile Manipulation with Visual-Force Goals;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. A Survey of Indoor 3D Reconstruction Based on RGB-D Cameras;IEEE Access;2024

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