A survey on deep learning techniques for image and video semantic segmentation
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 …
machine learning researchers. Many applications on the rise need accurate and efficient …
A review on deep learning techniques applied to semantic segmentation
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 …
machine learning researchers. Many applications on the rise need accurate and efficient …
Playing for data: Ground truth from computer games
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 …
large datasets. Unfortunately, creating large datasets with pixel-level labels has been …
The cityscapes dataset for semantic urban scene understanding
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 …
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
Vision-based semantic segmentation in urban scenarios is a key functionality for
autonomous driving. Recent revolutionary results of deep convolutional neural networks …
autonomous driving. Recent revolutionary results of deep convolutional neural networks …
Segflow: Joint learning for video object segmentation and optical flow
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 …
predicting pixel-wise object segmentation and optical flow in videos. The proposed SegFlow …
Efficientps: Efficient panoptic segmentation
Understanding the scene in which an autonomous robot operates is critical for its competent
functioning. Such scene comprehension necessitates recognizing instances of traffic …
functioning. Such scene comprehension necessitates recognizing instances of traffic …
Segnet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling
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 …
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
Semantic segmentation of large-scale outdoor point clouds is essential for urban scene
understanding in various applications, especially autonomous driving and urban high …
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 …
development of 3D point clouds. Semantic segmentation of point cloud, as a key step in …