segmentation result
Segment Anything in 3D with NeRFs
We refer to the proposed solution as SA3D, for Segment Anything in 3D. It is only required to provide a manual segmentation prompt ( e.g., rough points) for the target object in a single view, which is used to generate its 2D mask in this view with SAM.
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Technology:
- Information Technology > Artificial Intelligence > Vision (1.00)
- Information Technology > Sensing and Signal Processing > Image Processing (0.68)
- Information Technology > Artificial Intelligence > Natural Language (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
Technology:
Technology:
Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation
This work was completed while Xin Y uan was a PhD student at the University of Chicago.
Country:
- North America > United States > Illinois > Cook County > Chicago (0.24)
- North America > United States > California (0.04)
Industry:
- Information Technology (0.68)
- Transportation > Ground (0.46)
- Education > Educational Setting (0.34)
Technology:
Country:
- Asia > China > Guangdong Province > Shenzhen (0.04)
- Europe > Switzerland > Zürich > Zürich (0.04)
- Asia > China > Jiangsu Province > Nanjing (0.04)
Technology:
Country:
- Europe > Switzerland > Zürich > Zürich (0.04)
- Asia (0.04)
Technology:
