在目标检测领域，小样本目标检测（Few-Shot Object Detection, FSOD）一直是个“硬骨头”。传统的做法通常需要在大规模基类数据上预训练，再针对极少数的新类样本进行微调。但微调过程不仅耗时，还容易导致模型对新类样本过拟合。近日，来自澳门大学和英特灵达的研究团队提出了一种全新的框架—— FSOD-VFM 。

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

A comparison of the number of research papers in two types of COD, traditional and deep learning, within Image-level and Video-level applications. The bar chart shows the increase in overall research ...

Robots and autonomous vehicles can use 3D point clouds from LiDAR sensors and camera images to perform 3D object detection. However, current techniques that combine both types of data struggle to ...

AI normally needs to be trained on existing material to detect objects, but Meta has a way for the technology to spot items without help. The social media giant has published a "Segment Anything" AI ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A team of Microsoft and Huazhong University researchers this week ...