Multispectral Object Detection
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Benchmarks
Most implemented
Fully Convolutional Networks for Semantic Segmentation
$\mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection
Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems
Multispectral Deep Neural Networks for Pedestrian Detection
YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Multispectral Detection Transformer with Infrared-Centric Sensor Fusion
Papers
CFGPNet: Cross-Attention-Based Fused Gradient Programmed Network Framework for Multispectral Object Detection
Multispectral object detection combines visible and thermal imagery to improve perception under challenging illumination and environmental conditions. However, differences in modality appearance and reliability can intro…
Multispectral Object DetectionComputational EfficiencyFully Rotation-Equivariant Spectral-Spatial Learning for Multispectral Object Detection
Existing multispectral detectors are limited by discrete spectral processing, a scale-dependent shift in the relative reliability of spectral and spatial cues across pyramid levels, and the lack of explicit rotation-equi…
Multispectral Object DetectionDual Sparse Aggregation Transformer for Multispectral Object Detection
Transformer-based approaches have obtained excellent performance in multispectral object detection tasks due to their ability to model long-range dependencies and capture complementary information. However, previous tran…
Multispectral Object DetectionProgressive Pixel-Neighborhood Deformable Cross-Attention for Multispectral Object Detection
Effective cross-modal feature alignment and interaction are central challenges in multispectral object detection. Although global cross-attention provides strong long-range modeling ability, its quadratic complexity with…
Multispectral Object DetectionSemantic correspondenceLong-range modelingSpectraDINO: Modality-Conditioned Adaptation of RGB Vision Foundation Models Across Infrared Bands
Vision foundation models (VFMs) pretrained on large-scale RGB data provide strong general-purpose representations, yet infrared perception, which is essential for robotics and driving in low light and adverse weather, st…
Multispectral Object DetectionSemantic SegmentationBridging the RGB-IR Gap: Consensus and Discrepancy Modeling for Text-Guided Multispectral Detection
Text-guided multispectral object detection uses text semantics to guide semantic-aware cross-modal interaction between RGB and IR for more robust perception. However, notable limitations remain: (1) existing methods ofte…
Multispectral Object Detection