Dec 16, 2020 · In this thesis, we argue that it is crucial to design deep architectures that can operate in previously unseen visual domains and recognize ...
Introduction. 29. 1.1. Overview. 29. 1.1. Domain shift: generalizing to new visual domains. 31. 1.1.2. Semantic shift: breaking model's semantic limits.
This thesis argues that it is crucial to design deep architectures that can operate in previously unseen visual domains and recognize novel semantic concepts.
We first describe different solutions for generalizing to new visual domains, applying variants of normalization layers to multiple challenging settings e.g. ...
Towards Recognizing New Semantic Concepts in New Visual Domains
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Despite being the leading paradigm in computer vision, deep neural networks are inherently limited by the visual and semantic information contained in their training set. In this thesis, we aim to design deep models operating with previously... Google Books
Originally published: 2022
Author: Massimiliano Mancini
In this thesis, we argue that it is crucial to design deep architectures that can operate in previously unseen visual domains and recognize novel semantic ...
Towards Recognizing New Semantic Concepts in New Visual Domains ; Metti nel carrello ; formato: 16x23 ; formato elettronico: open access PDF ; pagine: 280 ; lingua:.
This work proposes a novel approach that learns domain-agnostic structured latent embeddings by projecting images from different domains.
Jul 23, 2020 · We presentCuMix (CurriculumMixup for recognizing unseen categories in unseen domains), a holistic algorithm to tackle ZSL, DG and ZSL+DG.
Dec 28, 2020 · To this end, recent works tried to empower visual object recognition methods with the capability to i) detect unseen concepts and ii) extended ...
Zero-Shot Learning aims to learn recognition models for recognizing new classes. The main strategy for ZSL is to associate source and target classes through an ...