Abstract: Salient object detection (SOD) in complex scenes and environments is a challenging research topic. Most works focus on RGB-based SOD, which limits its performance of real-life applications ...
OBER (OBject-Effect Removal) is a hybrid dataset designed to support research in object removal with effects, combining both camera-captured and simulated data. 🔥 We have released the full dataset ...
This is the offical implementation of paper Quasi-Dense Similarity Learning for Multiple Object Tracking. We present a trailer that consists of method illustrations and tracking visualizations. Our ...
Abstract: Referring camouflaged object detection (Ref-COD) is a recently proposed task, aiming to segment specified camouflaged objects by leveraging visual reference, i.e., a small set of referring ...
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