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3D Geometric Shape Assembly via Efficient Point Cloud Matching
Nahyuk Lee, Juhong Min, Junha Lee +4
Learning to assemble geometric shapes into a larger target structure is a pivotal task in various practical applications. In this work, we tackle this problem by establishing local…
Multi-view Image Prompted Multi-view Diffusion for Improved 3D Generation
Seungwook Kim, Yichun Shi, Kejie Li +2
Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D…
Learning SO(3)-Invariant Semantic Correspondence via Local Shape Transform
Chunghyun Park, Seungwook Kim, Jaesik Park +1
Establishing accurate 3D correspondences between shapes stands as a pivotal challenge with profound implications for computer vision and robotics. However, existing self-supervised…
CorrespondentDream: Enhancing 3D Fidelity of Text-to-3D using Cross-View Correspondences
Seungwook Kim, Kejie Li, Xueqing Deng +3
Leveraging multi-view diffusion models as priors for 3D optimization have alleviated the problem of 3D consistency, e.g., the Janus face problem or the content drift problem, in ze…