Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic Grasping

arXiv:2404.06277v1 Announce Type: new
Abstract: Foundation models are a strong trend in deep learning and computer vision. These models serve as a base for applications as they require minor or no further fine-tuning by developers to integrate into their applications. Foundation models for zero-shot object segmentation such as Segment Anything (SAM) output segmentation masks from images without any further object information. When they are followed in a pipeline by an object identification model, they can perform object detection without training. …

abstract applications arxiv computer computer vision cs.cv deep learning developers embeddings fine-tuning foundation grasping identification loss object robotic segmentation serve trend type vision zero-shot