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 …
performance of semantic segmentation has been greatly improved by using deep learning …
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 …
Google scanned objects: A high-quality dataset of 3d scanned household items
Interactive 3D simulations have enabled break-throughs in robotics and computer vision, but
simulating the broad diversity of environments needed for deep learning requires large …
simulating the broad diversity of environments needed for deep learning requires large …
Adabins: Depth estimation using adaptive bins
We address the problem of estimating a high quality dense depth map from a single RGB
input image. We start out with a baseline encoder-decoder convolutional neural network …
input image. We start out with a baseline encoder-decoder convolutional neural network …
Pointcontrast: Unsupervised pre-training for 3d point cloud understanding
Arguably one of the top success stories of deep learning is transfer learning. The finding that
pre-training a network on a rich source set (eg, ImageNet) can help boost performance once …
pre-training a network on a rich source set (eg, ImageNet) can help boost performance once …
Depthformer: Exploiting long-range correlation and local information for accurate monocular depth estimation
This paper aims to address the problem of supervised monocular depth estimation. We start
with a meticulous pilot study to demonstrate that the long-range correlation is essential for …
with a meticulous pilot study to demonstrate that the long-range correlation is essential for …
Self-supervised pretraining of 3d features on any point-cloud
Pretraining on large labeled datasets is a prerequisite to achieve good performance in many
computer vision tasks like image recognition, video understanding etc. However, pretraining …
computer vision tasks like image recognition, video understanding etc. However, pretraining …
Exploring data-efficient 3d scene understanding with contrastive scene contexts
The rapid progress in 3D scene understanding has come with growing demand for data;
however, collecting and annotating 3D scenes (eg point clouds) are notoriously hard. For …
however, collecting and annotating 3D scenes (eg point clouds) are notoriously hard. For …
UrbanLF: A comprehensive light field dataset for semantic segmentation of urban scenes
As one of the fundamental technologies for scene understanding, semantic segmentation
has been widely explored in the last few years. Light field cameras encode the geometric …
has been widely explored in the last few years. Light field cameras encode the geometric …
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 …