Papers Multispectral Object Detection
“Multispectral Object Detection” 태그가 달린 논문 52편 · 필터 해제
Rethinking Early-Fusion Strategies for Improved Multispectral Object Detection
Most recent multispectral object detectors employ a two-branch structure to extract features from RGB and thermal images. While the two-branch structure achieves better performance than a single-branch structure, it over…
Knowledge DistillationMultispectral Object Detectionobject-detectionObject Detection+1MiPa: Mixed Patch Infrared-Visible Modality Agnostic Object Detection
In real-world scenarios, using multiple modalities like visible (RGB) and infrared (IR) can greatly improve the performance of a predictive task such as object detection (OD). Multimodal learning is a common way to lever…
Autonomous DrivingMultispectral Object Detectionobject-detectionObject Detection+1UniRGB-IR: A Unified Framework for RGB-Infrared Semantic Tasks via Adapter Tuning
Semantic analysis on visible (RGB) and infrared (IR) images has gained attention for its ability to be more accurate and robust under low-illumination and complex weather conditions. Due to the lack of pre-trained founda…
Multispectral Object DetectionPedestrian DetectionThermal Image SegmentationCFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions
Cross-modality images that integrate visible-infrared spectra cues can provide richer complementary information for object detection. Despite this, existing visible-infrared object detection methods severely degrade in s…
MambaMultispectral Object DetectionObjectobject-detection+1A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)
Segment Anything Model (SAM) is drastically accelerating the speed and accuracy of automatically segmenting and labeling large Red-Green-Blue (RGB) imagery datasets. However, SAM is unable to segment and label images out…
Multispectral Object Detectionobject-detectionObject DetectionINSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian Detection
Pedestrian detection is a critical task for safety-critical systems, but detecting pedestrians is challenging in low-light and adverse weather conditions. Thermal images can be used to improve robustness by providing com…
Multispectral Object DetectionPedestrian DetectionRemoval then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection
In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse array of fields. By leveraging the comple…
Multispectral Object DetectionObjectobject-detectionObject Detection+2RGB-X Object Detection via Scene-Specific Fusion Modules
Multimodal deep sensor fusion has the potential to enable autonomous vehicles to visually understand their surrounding environments in all weather conditions. However, existing deep sensor fusion methods usually employ c…
Autonomous VehiclesMultispectral Object DetectionObjectobject-detection+2ICAFusion: 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. Previous studies have demonstrated the effectiveness of feature fusion using convolutional neural networks, but th…
Multispectral Object Detectionobject-detectionObject Detection$\mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection
Object detection on visible (RGB) and infrared (IR) images, as an emerging solution to facilitate robust detection for around-the-clock applications, has received extensive attention in recent years. With the help of IR …
2D Object DetectionMultispectral Object DetectionObjectobject-detection+1Multimodal Object Detection by Channel Switching and Spatial Attention
Multimodal object detection has attracted great attention in recent years since the information specific to different modalities can complement each other and effectively improve the accuracy and stability of the detecti…
Multispectral Object Detectionobject-detectionObject DetectionPedestrian DetectionTFDet: Target-Aware Fusion for RGB-T Pedestrian Detection
Pedestrian detection plays a critical role in computer vision as it contributes to ensuring traffic safety. Existing methods that rely solely on RGB images suffer from performance degradation under low-light conditions d…
Multispectral Object Detectionobject-detectionObject DetectionPedestrian DetectionTranslation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection
Integrating multispectral data in object detection, especially visible and infrared images, has received great attention in recent years. Since visible (RGB) and infrared (IR) images can provide complementary information…
2D Object Detectioncross-modal alignmentCrowd CountingMultispectral Object Detection+8Deep learning with RGB and thermal images onboard a drone for monitoring operations
This article describes the artificial intelligence (AI) component of a drone for monitoring and patrolling tasks associated with disaster relief missions in specific restricted disaster scenarios, as specified by the Adv…
Human DetectionMultispectral Object Detectionobject-detectionObject Detection+1Confidence-aware Fusion using Dempster-Shafer Theory for Multispectral Pedestrian Detection
Multispectral pedestrian detection is an important and valuable task in many applications, which could provide a more accurate and reliable pedestrian detection result by using the complementary visual information from c…
Multispectral Object DetectionPedestrian DetectionCMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
Scene understanding based on image segmentation is a crucial component of autonomous vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting complementary features from the supplementary mo…
3D Object DetectionAutonomous VehiclesCamouflaged Object SegmentationImage Manipulation Localization+8ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography
Advances in multi-spectral detectors are causing a paradigm shift in X-ray Computed Tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the o…
3D ReconstructionComputed Tomography (CT)Image ReconstructionInference Optimization+3Cross-Modality Fusion Transformer for Multispectral Object Detection
Multispectral image pairs can provide the combined information, making object detection applications more reliable and robust in the open world. To fully exploit the different modalities, we present a simple yet effectiv…
Multispectral Object DetectionObjectobject-detectionObject Detection+1A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection
Deep neural networks, especially convolutional deep neural networks, are state-of-the-art methods to classify, segment or even generate images, movies, or sounds. However, these methods lack of a good semantic understand…
Autonomous Drivingimage-classificationImage ClassificationMultispectral Object Detection+4LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
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. In this case, infrared and visi…
Image GenerationImage RegistrationImage-to-Image TranslationInfrared And Visible Image Fusion+6