Cremers, Daniel

Flownet: Learning optical flow with convolutional networks

Dosovitskiy, A., Fischer, P., Ilg, E., Hausser, P., Hazirbas, C., Golkov, V., Smagt, P. V. D., Cremers, D., & Brox, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 4,313

LSD-SLAM: Large-scale direct monocular SLAM

Engel, J., Schöps, T., & Cremers, D. (2014) · Lecture Notes in Computer Science

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 3,851

One-Shot Video Object Segmentation

Caelles, S., Maninis, K.-K., Pont-Tuset, J., Leal-Taixe, L., Cremers, D., & Van Gool, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 927

FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture

Hazirbas, C., Ma, L., Domokos, C., & Cremers, D. (2017) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 902

MOT20: A benchmark for multi object tracking in crowded scenes

Dendorfer, P., Rezatofighi, H., Milan, A., Shi, J., Cremers, D., Reid, I., Roth, S., Schindler, K., & Leal-Taixé, L. (2020) · arXiv

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 779

Image-Based Localization Using LSTMs for Structured Feature Correlation

Walch, F., Hazirbas, C., Leal-Taixe, L., Sattler, T., Hilsenbeck, S., & Cremers, D. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Robotics and Sensor-Based LocalizationAdvanced Image and Video Retrieval Techniques

Cited by 521

D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry

Yang, N., von Stumberg, L., Wang, R., & Cremers, D. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 438

MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking

Dendorfer, P., Os̆ep, A., Milan, A., Schindler, K., Cremers, D., Reid, I., Roth, S., & Leal-Taixé, L. (2021) · International Journal of Computer Vision

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 374

Video Object Segmentation without Temporal Information

Maninis, K.-K., Caelles, S., Chen, Y., Pont-Tuset, J., Leal-Taixe, L., Cremers, D., & Van Gool, L. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 354

Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry

Yang, N., Wang, R., Stückler, J., & Cremers, D. (2018) · Lecture Notes in Computer Science

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 346

Large-scale direct SLAM for omnidirectional cameras

Caruso, D., Engel, J., & Cremers, D. (2015) · 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 244

What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?

Mayer, N., Ilg, E., Fischer, P., Hazirbas, C., Cremers, D., Dosovitskiy, A., & Brox, T. (2018) · International Journal of Computer Vision

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 191

Radiomics in radiooncology – challenging the medical physicist

Peeken, J. C., Bernhofer, M., Wiestler, B., Goldberg, T., Cremers, D., Rost, B., Wilkens, J. J., Combs, S. E., & Nüsslin, F. (2018) · Physica Medica

Radiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education

Cited by 98

Duality TV-L1 flow with fundamental matrix prior

Wedel, A., Pock, T., Braun, J., Franke, U., & Cremers, D. (2008) · 2008 23rd International Conference Image and Vision Computing New Zealand

Advanced Vision and ImagingVideo Surveillance and Tracking Methods

Cited by 58

It’s a (Blind) Match! Towards Vision-Language Correspondence without Parallel Data

Schnaus, D., Araslanov, N., & Cremers, D. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1