Generalized Differentiable RANSAC
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00370527" target="_blank" >RIV/68407700:21230/23:00370527 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICCV51070.2023.01618" target="_blank" >https://doi.org/10.1109/ICCV51070.2023.01618</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCV51070.2023.01618" target="_blank" >10.1109/ICCV51070.2023.01618</a>
Alternative languages
Result language
angličtina
Original language name
Generalized Differentiable RANSAC
Original language description
We propose del-RANSAC, a generalized differentiable RANSAC that allows learning the entire randomized robust estimation pipeline. The proposed approach enables the use of relaxation techniques for estimating the gradients in the sampling distribution, which are then propagated through a differentiable solver. The trainable quality function marginalizes over the scores from all the models estimated within del-RANSAC to guide the network learning accurate and useful inlier probabilities or to train feature detection and matching networks. Our method directly maximizes the probability of drawing a good hypothesis, allowing us to learn better sampling distributions. We test del-RANSAC on various real-world scenarios on fundamental and essential matrix estimation, and 3D point cloud registration, outdoors and indoors, with handcrafted and learning-based features. It is superior to the state-of-the-art in terms of accuracy while running at a similar speed to its less accurate alternatives. The code and trained models are available at https://github.com/weitong8591/differentiable_ransac.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICCV2023: Proceedings of the International Conference on Computer Vision
ISBN
979-8-3503-0719-1
ISSN
1550-5499
e-ISSN
2380-7504
Number of pages
12
Pages from-to
17603-17614
Publisher name
IEEE
Place of publication
Piscataway
Event location
Paris
Event date
Oct 2, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001169500502021