Jang, W;
Agapito, L;
(2022)
CodeNeRF: Disentangled Neural Radiance Fields for Object Categories.
In:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
(pp. pp. 12929-12938).
IEEE: Montreal, QC, Canada.
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Abstract
CodeNeRF is an implicit 3D neural representation that learns the variation of object shapes and textures across a category and can be trained, from a set of posed images, to synthesize novel views of unseen objects. Unlike the original NeRF, which is scene specific, CodeNeRF learns to disentangle shape and texture by learning separate embeddings. At test time, given a single unposed image of an unseen object, CodeNeRF jointly estimates camera viewpoint, and shape and appearance codes via optimization. Unseen objects can be reconstructed from a single image, and then rendered from new viewpoints or their shape and texture edited by varying the latent codes. We conduct experiments on the SRN benchmark, which show that CodeNeRF generalises well to unseen objects and achieves on-par performance with methods that require known camera pose at test time. Our results on real-world images demonstrate that CodeNeRF can bridge the sim-to-real gap. Project page: https://github.com/wayne1123/code-nerf.
| Type: | Proceedings paper |
|---|---|
| Title: | CodeNeRF: Disentangled Neural Radiance Fields for Object Categories |
| Event: | 2021 IEEE/CVF International Conference on Computer Vision (ICCV) |
| Dates: | 10 Oct 2021 - 17 Oct 2021 |
| ISBN-13: | 9781665428125 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICCV48922.2021.01271 |
| Publisher version: | https://doi.org/10.1109/ICCV48922.2021.01271 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Computer vision, Codes, Three-dimensional displays, Shape, Image color analysis, Process control, Benchmark testing |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10147565 |
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