3 papers
cs.CV2024
Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications
Markus Hillemann, Robert Langendörfer, Max Heiken +6
Neural Radiance Fields (NeRFs) have become a rapidly growing research field with the potential to revolutionize typical photogrammetric workflows, such as those used for 3D scene r…
cs.CV2020
Uncertainty Estimation for End-To-End Learned Dense Stereo Matching via Probabilistic Deep Learning
Max Mehltretter
Motivated by the need to identify erroneous disparity assignments, various approaches for uncertainty and confidence estimation of dense stereo matching have been presented in rece…
cs.CV2019
CNN-based Cost Volume Analysis as Confidence Measure for Dense Matching
Max Mehltretter, Christian Heipke
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 dr…