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Computer Science > Computer Vision and Pattern Recognition

arXiv:2211.00722 (cs)
[Submitted on 1 Nov 2022]

Title:VIINTER: View Interpolation with Implicit Neural Representations of Images

Authors:Brandon Yushan Feng, Susmija Jabbireddy, Amitabh Varshney
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Abstract:We present VIINTER, a method for view interpolation by interpolating the implicit neural representation (INR) of the captured images. We leverage the learned code vector associated with each image and interpolate between these codes to achieve viewpoint transitions. We propose several techniques that significantly enhance the interpolation quality. VIINTER signifies a new way to achieve view interpolation without constructing 3D structure, estimating camera poses, or computing pixel correspondence. We validate the effectiveness of VIINTER on several multi-view scenes with different types of camera layout and scene composition. As the development of INR of images (as opposed to surface or volume) has centered around tasks like image fitting and super-resolution, with VIINTER, we show its capability for view interpolation and offer a promising outlook on using INR for image manipulation tasks.
Comments: SIGGRAPH Asia 2022
Subjects: Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR); Machine Learning (cs.LG)
Cite as: arXiv:2211.00722 [cs.CV]
  (or arXiv:2211.00722v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2211.00722
Related DOI: https://doi.org/10.1145/3550469.3555417

Submission history

From: Brandon Yushan Feng [view email]
[v1] Tue, 1 Nov 2022 19:51:30 UTC (33,244 KB)
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