A Survey of Trustworthy Representation Learning Across Domains
As AI systems have obtained significant performance to be deployed widely in our daily live
and human society, people both enjoy the benefits brought by these technologies and suffer …
and human society, people both enjoy the benefits brought by these technologies and suffer …
Insect-foundation: A foundation model and large-scale 1m dataset for visual insect understanding
In precision agriculture the detection and recognition of insects play an essential role in the
ability of crops to grow healthy and produce a high-quality yield. The current machine vision …
ability of crops to grow healthy and produce a high-quality yield. The current machine vision …
Fairness continual learning approach to semantic scene understanding in open-world environments
Continual semantic segmentation aims to learn new classes while maintaining the
information from the previous classes. Although prior studies have shown impressive …
information from the previous classes. Although prior studies have shown impressive …
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 …
Unsupervised Video Deraining with An Event Camera
Current unsupervised video deraining methods are inefficient in modeling the intricate
spatio-temporal properties of rain, which leads to unsatisfactory results. In this paper, we …
spatio-temporal properties of rain, which leads to unsatisfactory results. In this paper, we …
Fairness in visual clustering: A novel transformer clustering approach
Promoting fairness for deep clustering models in unsupervised clustering settings to reduce
demographic bias is a challenging goal. This is because of the limitation of large-scale …
demographic bias is a challenging goal. This is because of the limitation of large-scale …
Conda: Continual unsupervised domain adaptation learning in visual perception for self-driving cars
TD Truong, P Helton, A Moustafa… - Proceedings of the …, 2024 - openaccess.thecvf.com
Although unsupervised domain adaptation methods have achieved remarkable
performance in semantic scene segmentation these approaches remain impractical in real …
performance in semantic scene segmentation these approaches remain impractical in real …
FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding in Open World
Continual Learning in semantic scene segmentation aims to continually learn new unseen
classes in dynamic environments while maintaining previously learned knowledge. Prior …
classes in dynamic environments while maintaining previously learned knowledge. Prior …
Dual-teacher de-biasing distillation framework for multi-domain fake news detection
Multi-domain fake news detection aims to identify whether various news from different
domains is real or fake and has become urgent and important. However, existing methods …
domains is real or fake and has become urgent and important. However, existing methods …
Infproto-Powered Adaptive Classifier and Agnostic Feature Learning for Single Domain Generalization in Medical Images
Designing a single domain generalization (DG) framework that generalizes from one source
domain to arbitrary unseen domains is practical yet challenging in medical image …
domain to arbitrary unseen domains is practical yet challenging in medical image …