% generated by bibtexbrowser % % Encoding: UTF-8 @article{Engel-et-al-pami2018, author = {J. Engel and V. Koltun and D. Cremers}, title = { Direct Sparse Odometry}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, year = {2018}, month = {mar}, titleurl = {engel_et_al_pami2018.pdf}, keywords = {mono-ds,dso,directsparseodometry, vslam}, } @inproceedings{wang2017stereoDSO, title = {Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras}, author = {R. Wang and M. Schwörer and D. Cremers}, booktitle = {International Conference on Computer Vision (ICCV)}, year = {2017}, month = {October}, address = {Venice, Italy}, keywords = {dso, visual odometry, stereo, 3D reconstruction, stereodso}, } @inproceedings{yang2018dvso, author = {N. Yang and R. Wang and J. Stueckler and D. Cremers}, title = {Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2018}, month = {September}, award = {Oral Presentation}, keywords = {dso, dvso, deep learning, monocular depth estimation, semi-supervised learning, slam, visual odometry, vslam}, } @inproceedings{yang20d3vo, author = {N. Yang and L. von Stumberg and R. Wang and D. Cremers}, title = {D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2020}, eprint = {2003.01060}, eprinttype = {arXiv}, eprintclass = {cs.CV}, award = {Oral Presentation}, keywords = {dso,dvso, deep learning, monocular depth estimation, semi-supervised learning, slam, visual odometry,d3vo, vslam}, } @inproceedings{wimbauer2020monorec, title = {MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera}, author = {F. Wimbauer and N. Yang and L. von Stumberg and N. Zeller and D Cremers}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2021}, eprint = {2011.11814}, eprinttype = {arXiv}, eprintclass = {cs.CV}, keywords = {monorec, dvso, d3vo, mvs, deep learning, SLAM, vslam, reconstruction}, }