Fine-grained zero-shot learning: Advances, challenges, and prospects
Recent zero-shot learning (ZSL) approaches have integrated fine-grained analysis, ie, fine-
grained ZSL, to mitigate the commonly known seen/unseen domain bias and misaligned …
grained ZSL, to mitigate the commonly known seen/unseen domain bias and misaligned …
Drpt: Disentangled and recurrent prompt tuning for compositional zero-shot learning
Compositional Zero-shot Learning (CZSL) aims to recognize novel concepts composed of
known knowledge without training samples. Standard CZSL either identifies visual primitives …
known knowledge without training samples. Standard CZSL either identifies visual primitives …
Fed-fsnet: Mitigating non-iid federated learning via fuzzy synthesizing network
Federated learning (FL) has emerged as a promising privacy-preserving distributed
machine learning framework recently. It aims at collaboratively learning a shared global …
machine learning framework recently. It aims at collaboratively learning a shared global …
Estimation of Near-Instance-Level Attribute Bottleneck for Zero-Shot Learning
Abstract Zero-Shot Learning (ZSL) involves transferring knowledge from seen classes to
unseen classes by establishing connections between visual and semantic spaces …
unseen classes by establishing connections between visual and semantic spaces …
Parsnets: A parsimonious orthogonal and low-rank linear networks for zero-shot learning
This paper provides a novel parsimonious yet efficient design for zero-shot learning (ZSL),
dubbed ParsNets, where we are interested in learning a composition of on-device friendly …
dubbed ParsNets, where we are interested in learning a composition of on-device friendly …
Attribute-aware representation rectification for generalized zero-shot learning
Generalized Zero-shot Learning (GZSL) has yielded remarkable performance by designing
a series of unbiased visual-semantics mappings, wherein, the precision relies heavily on the …
a series of unbiased visual-semantics mappings, wherein, the precision relies heavily on the …
Fine-Grained Side Information Guided Dual-Prompts for Zero-Shot Skeleton Action Recognition
Skeleton-based zero-shot action recognition aims to recognize unknown human actions
based on the learned priors of the known skeleton-based actions and a semantic descriptor …
based on the learned priors of the known skeleton-based actions and a semantic descriptor …
Dual Expert Distillation Network for Generalized Zero-Shot Learning
Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-
to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping …
to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping …
Dental Severity Assessment through Few-shot Learning and SBERT Fine-tuning
M Dehghani - arXiv preprint arXiv:2402.15755, 2024 - arxiv.org
Dental diseases have a significant impact on a considerable portion of the population,
leading to various health issues that can detrimentally affect individuals' overall well-being …
leading to various health issues that can detrimentally affect individuals' overall well-being …
Query-Based Knowledge Sharing for Open-Vocabulary Multi-Label Classification
Identifying labels that did not appear during training, known as multi-label zero-shot
learning, is a non-trivial task in computer vision. To this end, recent studies have attempted …
learning, is a non-trivial task in computer vision. To this end, recent studies have attempted …