Review the state-of-the-art technologies of semantic segmentation based on deep learning
The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …
information and predict the semantic category of each pixel from a given label set. With the …
Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks
L Wang, KJ Yoon - IEEE transactions on pattern analysis and …, 2021 - ieeexplore.ieee.org
Deep neural models, in recent years, have been successful in almost every field, even
solving the most complex problem statements. However, these models are huge in size with …
solving the most complex problem statements. However, these models are huge in size with …
Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation
As acquiring pixel-wise annotations of real-world images for semantic segmentation is a
costly process, a model can instead be trained with more accessible synthetic data and …
costly process, a model can instead be trained with more accessible synthetic data and …
Source-free domain adaptation for semantic segmentation
Abstract Unsupervised Domain Adaptation (UDA) can tackle the challenge that
convolutional neural network (CNN)-based approaches for semantic segmentation heavily …
convolutional neural network (CNN)-based approaches for semantic segmentation heavily …
Semantic-aware domain generalized segmentation
Deep models trained on source domain lack generalization when evaluated on unseen
target domains with different data distributions. The problem becomes even more …
target domains with different data distributions. The problem becomes even more …