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 ...
OV-DQUO is an open-vocabulary detection framework that learns from open-world unknown objects through wildcard matching and contrastive denoising training methods, mitigating performance degradation ...
Abstract: Oriented object detection in remote sensing images is a challenging task due to objects being distributed in multiorientation. Recently, end-to-end transformer-based methods have achieved ...
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