arXiv:2402.02555v2 Announce Type: replace-cross Abstract: In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, the proposed dataset naming EntitySeg contains images spanning various image domains and entities, along with plentiful high-resolution images and high-quality mask annotations for training and testing. Then, the ESG mainly consists of two modules: CropFormer for high-quality entity segmentation whereas GELLA for accurate noun extraction from sentences and semantic matching between language and visu
Source: arXiv cs.CL — read the full report at the original publisher.