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The field of computer vision is surveyed and assessed, key research issues are identified, and possibilities for a future vision system are discussed. The problems of descriptions of two and three dimensional worlds are discussed.
Cunningham, R. +4 more
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IET Computer Vision, 2022 Despite recent advances in 3‐D pose estimation of human hands, thanks to the advent of convolutional neural networks (CNNs) and depth cameras, this task is still far from being solved in uncontrolled setups.
Meysam Madadi +3 more
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The Programming Historian, 2022 This is the second of a two-part lesson introducing deep learning based computer vision methods for humanities research. This lesson digs deeper into the details of training a deep learning based computer vision model.
Daniel van Strien +4 more
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QUANTITATIVE COMPARISON BETWEEN NEURAL NETWORK- AND SGM-BASED STEREO MATCHING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Over the last decades, various methods for three-dimensional detection of the environment have been developed and successfully used. This work considers classical stereo methods, which can determine depth information by the means of correspondence ...
A. Frenzel, N. Deckers, R. Reulke
doaj +1 more source
ROBUST AERIAL OBJECT TRACKING IN HIGH DYNAMIC FLIGHT MANEUVERS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 Integrating drones into the civil airspace is one of the biggest challenges for civil aviation, responsible authorities and involved com- panies around the world in the upcoming years. For a full integration into non-segregated airspace such a system has
A. Nussberger, H. Grabner, L. van Gool
doaj +1 more source
Sim-to-Real Transfer for Object Detection in Aerial Inspections of Transmission Towers
IEEE Access, 2023 Training deep learning models for object detection usually requires a large amount of data, a condition that is not common for most real-world applications, especially in the context of aerial imagery.
Augusto J. Peterlevitz +15 more
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The Programming Historian, 2022 This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Python library, the lesson walks through the pipeline of ...
Daniel van Strien +4 more
doaj +1 more source
A Convolutional Neural Network for Nonrigid Structure from Motion
International Journal of Digital Multimedia Broadcasting, 2022 In this study, we propose a reconstruction and optimization neural network (RONN), a novel neural network for nonrigid structure from motion, which is completed by an unsupervised convolution neural network.
Yaming Wang +3 more
doaj +1 more source
Investigating the Intelligibility of a Computer Vision System for Blind Users [PDF]
, 2020 Computer vision systems to help blind usersare becoming increasingly common yet often these systems are not intelligible. Our work investigates the intelligibility of a wearable computer vision system to help blind users locate and ...
Ahmed, S. +5 more
core +1 more source
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges [PDF]
, 2022 This paper describes the third Affective Behavior Analysis in-the-wild (ABAW) Competition, held in conjunction with IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) +1 more
core +3 more sources