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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





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.


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