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Multispectral Object Detection

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보존된 평가 기록: 38

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.

논문

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Multispectral Object Detection

논문

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework

Multispectral Detection Transformer with Infrared-Centric Sensor Fusion

Optimizing Multispectral Object Detection: A Bag of Tricks and Comprehensive Benchmarks

Surveying You Only Look Once (YOLO) Multispectral Object Detection Advancements, Applications And Challenges

When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Dataset

RGB-T Object Detection via Group Shuffled Multi-receptive Attention and Multi-modal Supervision

Rethinking Early-Fusion Strategies for Improved Multispectral Object Detection

MiPa: Mixed Patch Infrared-Visible Modality Agnostic Object Detection

UniRGB-IR: A Unified Framework for RGB-Infrared Semantic Tasks via Adapter Tuning

CFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions

A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)

Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection

RGB-X Object Detection via Scene-Specific Fusion Modules

ICAFusion: Iterative Cross-Attention Guided Feature Fusion for Multispectral Object Detection

$\mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection

TFDet: Target-Aware Fusion for RGB-T Pedestrian Detection

Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection

Confidence-aware Fusion using Dempster-Shafer Theory for Multispectral Pedestrian Detection

CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers

ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography

Cross-Modality Fusion Transformer for Multispectral Object Detection

A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

MLPD: Multi-Label Pedestrian Detector in Multispectral Domain

Multispectral Object Detection with Deep Learning

Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks

Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems

Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection

CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation

Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation

Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection

Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection

Multispectral Deep Neural Networks for Pedestrian Detection

Fully Convolutional Networks for Semantic Segmentation