3 accepted papers
Knowledge graph construction (KGC) aims to extract valuable information from text and organize it into structured knowledge graphs (KGs). Recent methods have leveraged the strong generative capabilities of large language models (LLMs) to improve the generalization and reduce the labor costs. However
We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image. SAM 3D excels in natural images, where occlusion and scene clutter are common and visual recognition cues from context play a larger role. We achieve th
Why don't we have foundation models in 3D yet? A key limitation is data scarcity. For 3D object part segmentation, existing datasets are small in size and lack diversity. We show that it is possible to break this data barrier by building a data engine powered by 2D foundation models. Our data engine…