Multispectral Object Detection
9 papers with code • 3 benchmarks • 2 datasets
Only using RGB cameras for automatic outdoor scene analysis is challenging when, for example, facing insufficient illumination or adverse weather. To improve the recognition reliability, multispectral systems add additional cameras (e.g. infra-red) and perform object detection from multispectral data. Although multispectral scene analysis with deep learning has be shown to have a great potential, there are still many open research questions and it has not been widely deployed in industrial contexts.
LLVIP
KAIST Multispectral Pedestrian Detection Benchmark
Most implemented papers
Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks
Multispectral images (e. g. visible and infrared) may be particularly useful when detecting objects with the same model in different environments (e. g. day/night outdoor scenes).
Guided Attentive Feature Fusion for Multispectral Pedestrian Detection
Multispectral image pairs can provide complementary visual information, making pedestrian detection systems more robust and reliable.
MLPD: Multi-Label Pedestrian Detector in Multispectral Domain
sejong-rcv/MLPD-Multi-Label-Pedestrian-Detection
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IEEE ROBOTICS AND AUTOMATION LETTERS 2021
In this letter, we tackle multispectral pedestrian detection, where all input data are not paired.
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
bupt-ai-cz/LLVIP
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It is very challenging for various visual tasks such as image fusion, pedestrian detection and image-to-image translation in low light conditions due to the loss of effective target areas.
Cross-Modality Fusion Transformer for Multispectral Object Detection
docf/multispectral-object-detection
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Multispectral image pairs can provide the combined information, making object detection applications more reliable and robust in the open world.
ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography
However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem.
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
huaaaliu/rgbx_semantic_segmentation
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Pixel-wise semantic segmentation of RGB images can be advanced by exploiting complementary features from the supplementary modality (X-modality).
ICAFusion: Iterative Cross-Attention Guided Feature Fusion for Multispectral Object Detection
Effective feature fusion of multispectral images plays a crucial role in multi-spectral object detection.
INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection
sejong-rcv/INSANet
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journal 2024
Extensive experiments demonstrate the effectiveness of the proposed methods, which achieve state-of-the-art performance on the KAIST dataset and LLVIP dataset.
