Unsupervised Cross-Modal Distillation for Thermal Infrared Tracking
Jingxian Sun, Lichao Zhang, Yufei Zha, Abel González-García, Peng Zhang, Wei Huang, Yanning Zhang
Abstract
The target representation learned by convolutional neural networks plays an important role in Thermal Infrared (TIR) tracking. Currently, most of the top-performing TIR trackers are still employing representations learned by the model trained on the RGB data. However, this representation does not take into account the information in the TIR modality itself, limiting the performance of TIR tracking.
Topics & Concepts
Computer scienceArtificial intelligenceTracking (education)Convolutional neural networkRepresentation (politics)BitTorrent trackerThermal infraredInfraredModality (human–computer interaction)Computer visionModalPattern recognition (psychology)LimitingEye trackingEngineeringOpticsPhysicsMaterials sciencePsychologyLawMechanical engineeringPoliticsPolitical sciencePolymer chemistryPedagogyVideo Surveillance and Tracking MethodsInfrared Target Detection MethodologiesInfrared Thermography in Medicine