The BRAVO Semantic Segmentation Challenge Results in UNCV2024
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00386220" target="_blank" >RIV/68407700:21230/25:00386220 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-91585-7_18" target="_blank" >https://doi.org/10.1007/978-3-031-91585-7_18</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-91585-7_18" target="_blank" >10.1007/978-3-031-91585-7_18</a>
Alternative languages
Result language
angličtina
Original language name
The BRAVO Semantic Segmentation Challenge Results in UNCV2024
Original language description
We propose the unified BRAVO challenge to benchmark the reliability of semantic segmentation models under realistic perturbations and unknown out-of-distribution (OOD) scenarios. We define two categories of reliability: (1) semantic reliability, which reflects the model's accuracy and calibration when exposed to various perturbations; and (2) OOD reliability, which measures the model's ability to detect object classes that are unknown during training. The challenge attracted nearly 100 submissions from international teams representing notable research institutions. The results reveal interesting insights into the importance of large-scale pre-training and minimal architectural design in developing robust and reliable semantic segmentation models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computer Vision – ECCV 2024, Part XVII
ISBN
978-3-031-91584-0
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
17
Pages from-to
290-306
Publisher name
Springer
Place of publication
Cham
Event location
Milano
Event date
Sep 29, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001544990200018