FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions (bibtex)
by T Yenamandra, A Tewari, N Yang, F Bernard, C Theobalt and D Cremers
Reference:
FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions (T Yenamandra, A Tewari, N Yang, F Bernard, C Theobalt and D Cremers), In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024. ([Project page],[ArXiv])
Bibtex Entry:
@inproceedings{yenamandra2024fire,
 author = {T Yenamandra and A Tewari and N Yang and F Bernard and C Theobalt and D Cremers},
 title = {FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions},
 booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
 month = {January},
 year = {2024},
 pages = {3077-3087},
}
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FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions (bibtex)
FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions (bibtex)
by T Yenamandra, A Tewari, N Yang, F Bernard, C Theobalt and D Cremers
Reference:
FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions (T Yenamandra, A Tewari, N Yang, F Bernard, C Theobalt and D Cremers), In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024. ([Project page],[ArXiv])
Bibtex Entry:
@inproceedings{yenamandra2024fire,
 author = {T Yenamandra and A Tewari and N Yang and F Bernard and C Theobalt and D Cremers},
 title = {FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions},
 booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
 month = {January},
 year = {2024},
 pages = {3077-3087},
}
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members:yangn

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Nan Yang

PhD student

Technical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: yangn@in.tum.de

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Research Interests

My research interests lie in incorporating deep learning into classical visual odometry and SLAM.

Brief Bio

Nan Yang received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications and his Master's degree in Informatics from the Technical University of Munich. Since May 2018, he is a Ph.D. student and senior computer vision researcher in Artisense, a startup co-founded by Prof. Daniel Cremers.

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