Abstract: Object detection (OD) is an essential and fundamental task in computer vision (CV) and satellite image processing. Existing deep learning methods have achieved impressive performance thanks ...

Abstract: Few-shot video object segmentation (FSVOS) aims to segment dynamic objects of unseen classes by resorting to a small set of support images that contain pixel-level object annotations.

This project aims to develop an object detection system for architectural floor plans using the YOLOv8 model. The system was trained to detect various elements commonly found in floor plans, such as ...

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 ...