A survey on deep learning techniques for image and video semantic segmentation

A Garcia-Garcia, S Orts-Escolano, S Oprea… - Applied Soft …, 2018 - Elsevier
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …

A review on deep learning techniques applied to semantic segmentation

A Garcia-Garcia, S Orts-Escolano, S Oprea… - arxiv preprint arxiv …, 2017 - arxiv.org
Image semantic segmentation is more and more being of interest for computer vision and
machine learning researchers. Many applications on the rise need accurate and efficient …

Playing for data: Ground truth from computer games

SR Richter, V Vineet, S Roth, V Koltun - … 11-14, 2016, Proceedings, Part II …, 2016 - Springer
Recent progress in computer vision has been driven by high-capacity models trained on
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …

The cityscapes dataset for semantic urban scene understanding

M Cordts, M Omran, S Ramos… - Proceedings of the …, 2016 - openaccess.thecvf.com
Visual understanding of complex urban street scenes is an enabling factor for a wide range
of applications. Object detection has benefited enormously from large-scale datasets …

The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes

G Ros, L Sellart, J Materzynska… - Proceedings of the …, 2016 - openaccess.thecvf.com
Vision-based semantic segmentation in urban scenarios is a key functionality for
autonomous driving. Recent revolutionary results of deep convolutional neural networks …

Segflow: Joint learning for video object segmentation and optical flow

J Cheng, YH Tsai, S Wang… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
This paper proposes an end-to-end trainable network, SegFlow, for simultaneously
predicting pixel-wise object segmentation and optical flow in videos. The proposed SegFlow …

Efficientps: Efficient panoptic segmentation

R Mohan, A Valada - International Journal of Computer Vision, 2021 - Springer
Understanding the scene in which an autonomous robot operates is critical for its competent
functioning. Such scene comprehension necessitates recognizing instances of traffic …

Segnet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling

V Badrinarayanan, A Handa, R Cipolla - arxiv preprint arxiv:1505.07293, 2015 - arxiv.org
We propose a novel deep architecture, SegNet, for semantic pixel wise image labelling.
SegNet has several attractive properties;(i) it only requires forward evaluation of a fully learnt …

Toronto-3D: A large-scale mobile LiDAR dataset for semantic segmentation of urban roadways

W Tan, N Qin, L Ma, Y Li, J Du, G Cai… - Proceedings of the …, 2020 - openaccess.thecvf.com
Semantic segmentation of large-scale outdoor point clouds is essential for urban scene
understanding in various applications, especially autonomous driving and urban high …

A review of deep learning-based semantic segmentation for point cloud

J Zhang, X Zhao, Z Chen, Z Lu - IEEE access, 2019 - ieeexplore.ieee.org
In recent years, the popularity of depth sensors and 3D scanners has led to a rapid
development of 3D point clouds. Semantic segmentation of point cloud, as a key step in …