Add to ORKGZero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen classes to the unseen classes. Existing methods of obtaining class semantics include manual attributes or automatic word vectors from language models (like word2vec). We know attribute annotation is costly, whereas automatic word-vectors are relatively noisy. To address this problem, we explore how ChatGPT, a large language model, can enhance class semantics for ZSL tasks. ChatGPT can be a helpful source to obtain text descriptions for each class containing related attributes and semantics. We use the word2vec model to get a word vector using the texts from ChatGPT. Then...
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their name...
Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space be...
Large-scale pre-trained Vision & Language (VL) models have shown remarkable performance in many appl...
Zero-shot learning relies on semantic class representations such as hand-engineered attributes or le...
Zero-Shot Learning (ZSL) aims at recognizing unseen classes that are absent during the training stag...
Generalized Zero-Shot Learning (GZSL) aims to train a classifier that can generalize to unseen class...
International audienceZero-shot learning aims to recognize instances of unseen classes, for which no...
Zero-shot learning (ZSL) tackles the novel class recognition problem by transferring semantic knowle...
Abstract Zero-shot learning (ZSL) models use semantic representations of visual classes to transfer ...
Zero-shot learning (ZSL) aims at recognizing classes for which no visual sample is available at trai...
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their name...
Zero-shot detection (ZSD) is a challenging task where we aim to recognize and localize objects simul...
Sufficient training examples are the fundamental requirement for most of the learning tasks. However...
Human beings have the remarkable ability to recognize novel visual objects only based on the descrip...
This is the author accepted mansucript.Zero-Shot Learning (ZSL) aims to recognise unseen object clas...
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their name...
Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space be...
Large-scale pre-trained Vision & Language (VL) models have shown remarkable performance in many appl...
Zero-shot learning relies on semantic class representations such as hand-engineered attributes or le...
Zero-Shot Learning (ZSL) aims at recognizing unseen classes that are absent during the training stag...
Generalized Zero-Shot Learning (GZSL) aims to train a classifier that can generalize to unseen class...
International audienceZero-shot learning aims to recognize instances of unseen classes, for which no...
Zero-shot learning (ZSL) tackles the novel class recognition problem by transferring semantic knowle...
Abstract Zero-shot learning (ZSL) models use semantic representations of visual classes to transfer ...
Zero-shot learning (ZSL) aims at recognizing classes for which no visual sample is available at trai...
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their name...
Zero-shot detection (ZSD) is a challenging task where we aim to recognize and localize objects simul...
Sufficient training examples are the fundamental requirement for most of the learning tasks. However...
Human beings have the remarkable ability to recognize novel visual objects only based on the descrip...
This is the author accepted mansucript.Zero-Shot Learning (ZSL) aims to recognise unseen object clas...
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their name...
Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space be...
Large-scale pre-trained Vision & Language (VL) models have shown remarkable performance in many appl...