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Found 7 papers, 3 papers with code
Leveraging Topology for Domain Adaptive Road Segmentation in Satellite and Aerial Imagery
In this work, we propose a topology-aware unsupervised domain adaptation approach for road segmentation in remote sensing imagery.
Distribution Regularized Self-Supervised Learning for Domain Adaptation of Semantic Segmentation
Due to the domain shift, this decision boundary is unaligned in the target domain, resulting in noisy pseudo labels adversely affecting self-supervised domain adaptation.
FogAdapt: Self-Supervised Domain Adaptation for Semantic Segmentation of Foggy Images
We propose a self-entropy and multi-scale information augmented self-supervised domain adaptation method (FogAdapt) to minimize the domain shift in foggy scenes segmentation.
Ranked #1 on
Domain Adaptation
on SYNTHIA-to-FoggyCityscapes
Weakly Supervised Domain Adaptation for Built-up Region Segmentation in Aerial and Satellite Imagery
We thoroughly study the limitations of existing domain adaptation methods and propose a weakly-supervised adaptation strategy where we assume image-level labels are available for the target domain.
Analysis of Compression Techniques for DNA Sequence Data
On the other hand, traditional compression techniques are also not much suitable for the compression of these types of sequential data.
MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling
Thus helping latent space learn the representation even when there are very few pixels belonging to the domain category (small object for example) compared to rest of the image.
Leveraging Orientation for Weakly Supervised Object Detection with Application to Firearm Localization
The OAOD algorithm is evaluated on the ITUF dataset and compared with current state-of-the-art object detectors, including fully supervised oriented object detectors.
