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iNeRF, Experiments - Coggle Diagram
iNeRF
Motivation
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given an image, find the translation and rotation of a camera relative to a 3D object or scene.
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Experiment
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We then show that for complex real-world scenes from the LLFF dataset, iNeRF can improve NeRF by estimating the camera poses of novel images and using these images as additional training data for NeRF
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Finally, we show iNeRF can perform category-level object pose estimation, including object instances not seen during training, with RGB images by inverting a NeRF model inferred from a single view
INeRF formulation
- Gradient-Based SE(3) Optimization
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NeRF: T, I —> theta
iNeRF: I, theta —> T
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Experiments
Synthetic dataset
For each scene, choose 5 test images and generate 5 different pose initializations???
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ShapeNet-SRN Cars
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Dataset Details:
1) using the "car" classes of ShapeNet introduced by Stizmann including 3514 cars.
2) split the 3514 cars into training, validation and test set.
3) for objects in the test set, we render an image in an archimedean spiral and then select another image within certain offset.
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