3D shape, segmentation, appearance, and object poses from images using neural fields with PNF
3D shape, segmentation, appearance, and object poses from images using neural fields with PNF
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation
arXiv paper abstract https://arxiv.org/abs/2205.04334v1
arXiv PDF paper https://arxiv.org/pdf/2205.04334v1.pdf
... present Panoptic Neural Fields (PNF), an object-aware neural scene representation that decomposes a scene into a set of objects (things) and background (stuff).
Each object is represented by an oriented 3D bounding box and a multi-layer perceptron (MLP) that takes position, direction, and time and outputs density and radiance.
The background stuff is represented by a similar MLP that additionally outputs semantic labels.
... model builds a panoptic radiance field representation of any scene from just color images.
... use off-the-shelf algorithms to predict camera poses, object tracks, and 2D image semantic segmentations.
... model can be used effectively for several tasks like novel view synthesis, 2D panoptic segmentation, 3D scene editing, and multiview depth prediction.
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