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Found 4 papers, 0 papers with code
Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
As input, NeRFs require multi-view images with corresponding camera poses as well as the interior orientation.
Image-based Deep Learning for the time-dependent prediction of fresh concrete properties
In this paper, a method is presented that makes it possible to predict the properties of fresh concrete during the mixing process based on stereoscopic image sequences of the concretes flow behaviour.
Uncertainty Estimation for End-To-End Learned Dense Stereo Matching via Probabilistic Deep Learning
Based on the well-known and commonly employed GC-Net architecture, a novel probabilistic neural network is presented, for the task of joint depth and uncertainty estimation from epipolar rectified stereo image pairs.
CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching
Due to its capability to identify erroneous disparity assignments in dense stereo matching, confidence estimation is beneficial for a wide range of applications, e. g. autonomous driving, which needs a high degree of confidence as mandatory prerequisite.
