Getting 3D shapes from a single image
Getting 3D shapes from a single image
Shelf-Supervised Mesh Prediction in the Wild
arXiv paper abstract https://arxiv.org/abs/2102.06195
arXiv PDF paper https://arxiv.org/pdf/2102.06195.pdf
Project Web page https://judyye.github.io/ShSMesh
We aim to infer 3D shape and pose of object from a single image and propose a learning-based approach that can train from unstructured image collections, supervised by only segmentation outputs from off-the-shelf recognition systems (i.e. 'shelf-supervised').
We first infer a volumetric representation in a canonical frame, along with the camera pose.
... The coarse volumetric prediction is then converted to a mesh-based representation, which is further refined in the predicted camera frame.
... We examine the method on both synthetic and real-world datasets and demonstrate its scalability on 50 categories in the wild, an order of magnitude more classes than existing works.
Please like and share this post if you enjoyed it using the buttons at the bottom!
Stay up to date. Subscribe to my posts https://morrislee1234.wixsite.com/website/contact
Web site with my other posts by category https://morrislee1234.wixsite.com/website
Comments