CVPR 2024 - FGVC11 Workshop

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43973935" target="_blank" >RIV/49777513:23520/24:43973935 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

CVPR 2024 - FGVC11 Workshop

Original language description

It may be tempting to think that image classification is a solved problem. However, one only needs to look at the poor performance of existing techniques in domains with limited training data and highly similar categories to see that this is not the case. In particular, fine-grained categorization, e.g., the precise differentiation between similar plant or animal species, disease of the retina, architectural styles, etc., is an extremely challenging problem, pushing the limits of both human and machine performance. In these domains, expert knowledge is typically required, and the question that must be addressed is how we can develop artificial systems that can efficiently discriminate between large numbers of highly similar visual concepts.The 11th Workshop on Fine-Grained Visual Categorization (FGVC11) will explore topics related to supervised learning, self-supervised learning, semi-supervised learning, vision and language, matching, localization, domain adaptation, transfer learning, few-shot learning, machine teaching, multimodal learning (e.g., audio and video), 3D-vision, crowd-sourcing, image captioning and generation, out-of-distribution detection, anomaly detection, open-set recognition, human-in-the-loop learning, and taxonomic prediction, all through the lens of fine-grained understanding. Hence, the relevant topics are neither restricted to vision nor categorization.

Czech name

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Czech description

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Type

W - Workshop organization

CEP classification

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OECD FORD branch

20205 - Automation and control systems

Project

<a href="/en/project/SS05010008" target="_blank" >SS05010008: Detection, identification and monitoring of animals by advanced computer vision methods.</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Event location

Seattle

Event country

US - UNITED STATES

Event starting date

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Event ending date

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Total number of attendees

100

Foreign attendee count

99

Type of event by attendee nationality

WRD - Celosvětová akce