DocF/multispectral-object-detection
A deep learning research project implementing a Transformer-based cross-modality fusion approach for object detection across RGB and thermal image modalities.
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This repository implements the Cross-Modality Fusion Transformer (CFT) for multispectral object detection, combining RGB and thermal image data. The approach uses Transformer self-attention mechanisms to learn long-range dependencies and perform both intra-modality and inter-modality fusion during feature extraction. Built on YOLOv5, the method improves robustness of object detection in real-world scenarios by leveraging complementary information from different imaging modalities.
Frequently asked
- What is DocF/multispectral-object-detection?
- A deep learning research project implementing a Transformer-based cross-modality fusion approach for object detection across RGB and thermal image modalities.
- Is multispectral-object-detection open source?
- Yes — DocF/multispectral-object-detection is open source, released under the AGPL-3.0 license.
- What language is multispectral-object-detection written in?
- DocF/multispectral-object-detection is primarily written in Python.
- How popular is multispectral-object-detection?
- DocF/multispectral-object-detection has 471 stars on GitHub.
- Where can I find multispectral-object-detection?
- DocF/multispectral-object-detection is on GitHub at https://github.com/DocF/multispectral-object-detection.