Search Results for author:
Found 4 papers, 2 papers with code
Plasticine3D: Non-rigid 3D editting with text guidance
Firstly, our work divides the editing process into a geometry editing stage and a texture editing stage to achieve more detailed and photo-realistic results ; Secondly, in order to perform non-rigid transformation with controllable results while maintain the fidelity towards original 3D models in the same time, we propose a multi-view-embedding(MVE) optimization strategy to ensure that the diffusion model learns the overall features of the original object and an embedding-fusion(EF) to control the degree of editing by adjusting the value of the fusing rate.
Korean Named Entity Recognition Based on Language-Specific Features
In the paper, we propose a novel way of improving named entity recognition in the Korean language using its language-specific features.
Contrastive Learning enhanced Author-Style Headline Generation
In this paper, we propose a novel Seq2Seq model called CLH3G (Contrastive Learning enhanced Historical Headlines based Headline Generation) which can use the historical headlines of the articles that the author wrote in the past to improve the headline generation of current articles.
Yet Another Format of Universal Dependencies for Korean
In this study, we propose a morpheme-based scheme for Korean dependency parsing and adopt the proposed scheme to Universal Dependencies.
