3 accepted papers
In this paper, we present FSOD-VFM: Few-Shot Object Detectors with Vision Foundation Models, a framework that leverages vision foundation models to tackle the challenge of few-shot object detection. FSOD-VFM integrates three key components: a universal proposal network (UPN) for category-agnostic bo…
Fully test-time adaptation (FTTA) is to adapt a model trained on a source domain to a target domain during the testing phase. Traditional methods like entropy minimization primarily focus on reducing uncertainty in output predictions, yet often overlook the diversity in target prediction results, wh…
In image stitching, artifacts caused by misalignment affect the visual quality and the performance of subsequent tasks such as segmentation and detection. This paper proposes SMPR, a reconstruction-based aligned image composition method to minimize artifacts. SMPR fuses images in part of the overlap…