Papers Thermal Infrared Object Tracking
“Thermal Infrared Object Tracking” 태그가 달린 논문 12편 · 필터 해제
Progressive Domain Adaptation for Thermal Infrared Object Tracking
Due to the lack of large-scale labeled Thermal InfraRed (TIR) training datasets, most existing TIR trackers are trained directly on RGB datasets. However, tracking methods trained on RGB datasets suffer a significant dro…
Domain AdaptationObjectObject TrackingSubdomain adaptation+1In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking
Deep learning-based methods monopolize the latest research in the field of thermal infrared (TIR) object tracking. However, relying solely on deep learning models to obtain better tracking results requires carefully sele…
ObjectObject TrackingThermal Infrared Object TrackingRoboflow 100: A Rich, Multi-Domain Object Detection Benchmark
The evaluation of object detection models is usually performed by optimizing a single metric, e.g. mAP, on a fixed set of datasets, e.g. Microsoft COCO and Pascal VOC. Due to image retrieval and annotation costs, these d…
2D Object DetectionImage RetrievalMedical Object DetectionMulti-Object Tracking+14LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
In this paper, we present a Large-Scale and high-diversity general Thermal InfraRed (TIR) Object Tracking Benchmark, called LSOTBTIR, which consists of an evaluation dataset and a training dataset with a total of 1,400 T…
DiversityObject TrackingThermal Infrared Object TrackingVocal Bursts Intensity PredictionMulti-Task Driven Feature Models for Thermal Infrared Tracking
Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of RGB trackers for representation. However, these feature models learned on RGB images are neither effective in representing TIR objects nor t…
Thermal Infrared Object TrackingLearning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
Existing deep Thermal InfraRed (TIR) trackers only use semantic features to describe the TIR object, which lack the sufficient discriminative capacity for handling distractors. This becomes worse when the feature extract…
Object TrackingSemantic SimilarityThermal Infrared Object TrackingLarge Margin Structured Convolution Operator for Thermal Infrared Object Tracking
Compared with visible object tracking, thermal infrared (TIR) object tracking can track an arbitrary target in total darkness since it cannot be influenced by illumination variations. However, there are many unwanted att…
ObjectObject TrackingThermal Infrared Object TrackingDeep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns
We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a l…
Material ClassificationMaterial RecognitionThermal Infrared Object TrackingPTB-TIR: A Thermal Infrared Pedestrian Tracking Benchmark
Thermal infrared (TIR) pedestrian tracking is one of the important components among numerous applications of computer vision, which has a major advantage: it can track pedestrians in total darkness. The ability to evalua…
AttributeThermal Infrared Object TrackingHierarchical Spatial-aware Siamese Network for Thermal Infrared Object Tracking
Most thermal infrared (TIR) tracking methods are discriminative, treating the tracking problem as a classification task. However, the objective of the classifier (label prediction) is not coupled to the objective of the …
General ClassificationObject TrackingThermal Infrared Object TrackingDeep Convolutional Neural Networks for Thermal Infrared Object Tracking
Unlike the visual object tracking, thermal infrared object tracking can track a target object in total darkness. Therefore, it has broad applications, such as in rescue and video surveillance at night. However, there are…
ObjectObject TrackingThermal Infrared Object TrackingVisual Object Tracking+1Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging
The ability to monitor respiratory rate is extremely important for medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake every day activities, are required.…
Physiological ComputingQuantizationThermal Infrared Object Tracking