DARE-GRAM: Unsupervised domain adaptation regression by aligning inverse gram matrices
Abstract Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain
gap between a labeled source dataset and an unlabelled target dataset for regression …
gap between a labeled source dataset and an unlabelled target dataset for regression …
Adaptive mutual learning for unsupervised domain adaptation
Unsupervised domain adaptation aims to transfer knowledge from labeled source domain to
unlabeled target domain. The semi-supervised method based on mean-teacher framework …
unlabeled target domain. The semi-supervised method based on mean-teacher framework …
Disentangled representation learning with causality for unsupervised domain adaptation
Most efforts in unsupervised domain adaptation (UDA) focus on learning the domain-
invariant representations between the two domains. However, such representations may still …
invariant representations between the two domains. However, such representations may still …
Gradual domain adaptation: Theory and algorithms
Unsupervised domain adaptation (UDA) adapts a model from a labeled source domain to an
unlabeled target domain in a one-off way. Though widely applied, UDA faces a great …
unlabeled target domain in a one-off way. Though widely applied, UDA faces a great …
An In-Depth Analysis of Domain Adaptation in Computer and Robotic Vision
This review article comprehensively delves into the rapidly evolving field of domain
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …
GeoMultiTaskNet: remote sensing unsupervised domain adaptation using geographical coordinates
Land cover maps are a pivotal element in a wide range of Earth Observation (EO)
applications. However, annotating large datasets to develop supervised systems for remote …
applications. However, annotating large datasets to develop supervised systems for remote …
Unsupervised domain adaptation via domain-adaptive diffusion
Unsupervised Domain Adaptation (UDA) is quite challenging due to the large distribution
discrepancy between the source domain and the target domain. Inspired by diffusion models …
discrepancy between the source domain and the target domain. Inspired by diffusion models …
Towards Adaptive Multi-Scale Intermediate Domain via Progressive Training for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) involves the transfer of knowledge from a labelled
source domain to an unlabelled target domain. Recent studies have introduced the concept …
source domain to an unlabelled target domain. Recent studies have introduced the concept …
From Canteen Food to Daily Meals: Generalizing Food Recognition to More Practical Scenarios
The precise recognition of food categories plays a pivotal role for intelligent health
management, attracting significant research attention in recent years. Prominent …
management, attracting significant research attention in recent years. Prominent …
Combining inherent knowledge of vision-language models with unsupervised domain adaptation through strong-weak guidance
Unsupervised domain adaptation (UDA) tries to overcome the tedious work of labeling data
by leveraging a labeled source dataset and transferring its knowledge to a similar but …
by leveraging a labeled source dataset and transferring its knowledge to a similar but …