Point2Lane: Polyline-based reconstruction with principal points for lane detection
In this work, we observed that a nonlinear line could be expressed with a set of linear lines.
We propose a novel lane detection method with polyline-based reconstruction based on this …
We propose a novel lane detection method with polyline-based reconstruction based on this …
Learning CNN on ViT: A Hybrid Model to Explicitly Class-specific Boundaries for Domain Adaptation
BH Ngo, NT Do-Tran, TN Nguyen… - Proceedings of the …, 2024 - openaccess.thecvf.com
Most domain adaptation (DA) methods are based on either a convolutional neural networks
(CNNs) or a vision transformers (ViTs). They align the distribution differences between …
(CNNs) or a vision transformers (ViTs). They align the distribution differences between …
Dual dynamic consistency regularization for semi-supervised domain adaptation
The Vision Transformer (ViT) model serves as a powerful model to capture and comprehend
global information, particularly when trained on extensive datasets. Conversely, the …
global information, particularly when trained on extensive datasets. Conversely, the …
Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias
Abstract Domain adaptation is a critical task in machine learning that aims to improve model
performance on a target domain by leveraging knowledge from a related source domain. In …
performance on a target domain by leveraging knowledge from a related source domain. In …
Multiple Tasks-Based Multi-Source Domain Adaptation Using Divide-and-Conquer Strategy
In single-source unsupervised domain adaptation (SUDA), it is often assumed that a single-
source domain can cover all target domain features. However, the limitation of labeled …
source domain can cover all target domain features. However, the limitation of labeled …