Methods and datasets on semantic segmentation: A review

H Yu, Z Yang, L Tan, Y Wang, W Sun, M Sun, Y Tang - Neurocomputing, 2018‏ - Elsevier
Semantic segmentation, also called scene labeling, refers to the process of assigning a
semantic label (eg car, people, and road) to each pixel of an image. It is an essential data …

Minimizing nonsubmodular functions with graph cuts-a review

V Kolmogorov, C Rother - IEEE transactions on pattern …, 2007‏ - ieeexplore.ieee.org
Optimization techniques based on graph cuts have become a standard tool for many vision
applications. These techniques allow to minimize efficiently certain energy functions …

Semantickitti: A dataset for semantic scene understanding of lidar sequences

J Behley, M Garbade, A Milioto… - Proceedings of the …, 2019‏ - openaccess.thecvf.com
Semantic scene understanding is important for various applications. In particular, self-driving
cars need a fine-grained understanding of the surfaces and objects in their vicinity. Light …

Maskfusion: Real-time recognition, tracking and reconstruction of multiple moving objects

M Runz, M Buffier, L Agapito - 2018 IEEE international …, 2018‏ - ieeexplore.ieee.org
We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM
system that goes beyond traditional systems which output a purely geometric map of a static …

Deep projective 3D semantic segmentation

FJ Lawin, M Danelljan, P Tosteberg, G Bhat… - Computer Analysis of …, 2017‏ - Springer
Semantic segmentation of 3D point clouds is a challenging problem with numerous real-
world applications. While deep learning has revolutionized the field of image semantic …

Statistical relational artificial intelligence: Logic, probability, and computation

LD Raedt, K Kersting, S Natarajan, D Poole - Synthesis lectures on …, 2016‏ - Springer
An intelligent agent interacting with the real world will encounter individual people, courses,
test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of …

Real-time human pose recognition in parts from single depth images

J Shotton, A Fitzgibbon, M Cook, T Sharp… - CVPR …, 2011‏ - ieeexplore.ieee.org
We propose a new method to quickly and accurately predict 3D positions of body joints from
a single depth image, using no temporal information. We take an object recognition …

Contextual classification of lidar data and building object detection in urban areas

J Niemeyer, F Rottensteiner, U Soergel - ISPRS journal of photogrammetry …, 2014‏ - Elsevier
In this work we address the task of the contextual classification of an airborne LiDAR point
cloud. For that purpose, we integrate a Random Forest classifier into a Conditional Random …

3D point cloud segmentation: A survey

A Nguyen, B Le - 2013 6th IEEE conference on robotics …, 2013‏ - ieeexplore.ieee.org
3D point cloud segmentation is the process of classifying point clouds into multiple
homogeneous regions, the points in the same region will have the same properties. The …

Real-time human pose recognition in parts from single depth images

J Shotton, T Sharp, A Kipman, A Fitzgibbon… - Communications of the …, 2013‏ - dl.acm.org
We propose a new method to quickly and accurately predict human pose---the 3D positions
of body joints---from a single depth image, without depending on information from preceding …