A survey on deep learning and its applications

S Dong, P Wang, K Abbas - Computer Science Review, 2021‏ - Elsevier
Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

Image segmentation using deep learning: A survey

S Minaee, Y Boykov, F Porikli, A Plaza… - IEEE transactions on …, 2021‏ - ieeexplore.ieee.org
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

2dpass: 2d priors assisted semantic segmentation on lidar point clouds

X Yan, J Gao, C Zheng, C Zheng, R Zhang… - European conference on …, 2022‏ - Springer
As camera and LiDAR sensors capture complementary information in autonomous driving,
great efforts have been made to conduct semantic segmentation through multi-modality data …

Self-support few-shot semantic segmentation

Q Fan, W Pei, YW Tai, CK Tang - European Conference on Computer …, 2022‏ - Springer
Existing few-shot segmentation methods have achieved great progress based on the
support-query matching framework. But they still heavily suffer from the limited coverage of …

Vitaev2: Vision transformer advanced by exploring inductive bias for image recognition and beyond

Q Zhang, Y Xu, J Zhang, D Tao - International Journal of Computer Vision, 2023‏ - Springer
Vision transformers have shown great potential in various computer vision tasks owing to
their strong capability to model long-range dependency using the self-attention mechanism …

Perturbed and strict mean teachers for semi-supervised semantic segmentation

Y Liu, Y Tian, Y Chen, F Liu… - Proceedings of the …, 2022‏ - openaccess.thecvf.com
Consistency learning using input image, feature, or network perturbations has shown
remarkable results in semi-supervised semantic segmentation, but this approach can be …

Vitae: Vision transformer advanced by exploring intrinsic inductive bias

Y Xu, Q Zhang, J Zhang, D Tao - Advances in neural …, 2021‏ - proceedings.neurips.cc
Transformers have shown great potential in various computer vision tasks owing to their
strong capability in modeling long-range dependency using the self-attention mechanism …

Polarized self-attention: Towards high-quality pixel-wise regression

H Liu, F Liu, X Fan, D Huang - arxiv preprint arxiv:2107.00782, 2021‏ - arxiv.org
Pixel-wise regression is probably the most common problem in fine-grained computer vision
tasks, such as estimating keypoint heatmaps and segmentation masks. These regression …

Strip pooling: Rethinking spatial pooling for scene parsing

Q Hou, L Zhang, MM Cheng… - Proceedings of the IEEE …, 2020‏ - openaccess.thecvf.com
Spatial pooling has been proven highly effective to capture long-range contextual
information for pixel-wise prediction tasks, such as scene parsing. In this paper, beyond …

A brief survey on semantic segmentation with deep learning

S Hao, Y Zhou, Y Guo - Neurocomputing, 2020‏ - Elsevier
Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …