Zero-Shot Object Proposals

Zero-Shot Object Proposals is a computer vision technique that aims to generate proposals for object instances in images without requiring any training data for specific object categories. Instead, it relies on a prior knowledge base of object attributes, such as color, shape, and texture, to generate proposals for object instances in an image. This approach allows for the detection of novel, unseen object categories and can be useful in applications such as image retrieval and scene understanding. Zero-Shot Object Proposals typically involves a combination of techniques such as object segmentation, feature extraction, and clustering to generate object proposals.