Abstract: Open world object detection (OWOD) aims to identify both known instances of trained classes and unknown ones. Despite recent advancements, existing methods exhibit a detection bias towards ...
Note: uvx pywho is not recommended — it runs inside uv's ephemeral sandbox, so the output reflects that temporary environment instead of your actual project. Always install pywho into the environment ...
Abstract: Monocular 3D object detection has gained considerable attention because of its cost-effectiveness and practical applicability, particularly in autonomous driving and robotics. Most of ...
face-mask-detection/ ├── dataset/ │ ├── with_mask/ # Training images with masks │ └── without_mask/ # Training images without masks ├── model/ │ ├── mask_detector.h5 # Trained model (generated) │ └── ...
Abstract: Camouflaged Object Detection (COD) involves identifying and segmenting objects that become part of the background. It is a complicated task for Computer Vision, which requires techniques ...
Abstract: Small object detection in remote sensing images remains challenging due to limited feature resolution and complex backgrounds. Conventional detectors, due to fixed receptive fields and ...
Abstract: Object Object detection, a fundamental task in computer vision, has undergone a revolutionary transformation with the advent of deep learning. This paper provides a comprehensive review of ...
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