23 citations · 40 across the 27 of their papers we have counts for
27 papers · 1 filter
Local Attention Transformers for High-Detail Optical Flow Upsampling
Alexander Gielisse, Nergis Tömen, Jan van Gemert
Most recent works on optical flow use convex upsampling as the last step to obtain high-resolution flow. In this work, we show and discuss several issues and limitations of this cu…
Aligning Object Detector Bounding Boxes with Human Preference
Ombretta Strafforello, Osman S. Kayhan, Oana Inel +2
Previous work shows that humans tend to prefer large bounding boxes over small bounding boxes with the same IoU. However, we show here that commonly used object detectors predict l…
MSD: A Benchmark Dataset for Floor Plan Generation of Building Complexes
Casper van Engelenburg, Fatemeh Mostafavi, Emanuel Kuhn +5
Diverse and realistic floor plan data are essential for the development of useful computer-aided methods in architectural design. Today's large-scale floor plan datasets predominan…
VIPriors 4: Visual Inductive Priors for Data-Efficient Deep Learning Challenges
Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios +4
The fourth edition of the "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" workshop features two data-impaired challenges. These challenges address the problem…
Deep Continuous Networks
Nergis Tomen, Silvia L. Pintea, Jan C. van Gemert
CNNs and computational models of biological vision share some fundamental principles, which opened new avenues of research. However, fruitful cross-field research is hampered by co…
Do Object Detection Localization Errors Affect Human Performance and Trust?
Sven de Witte, Ombretta Strafforello, Jan van Gemert
Bounding boxes are often used to communicate automatic object detection results to humans, aiding humans in a multitude of tasks. We investigate the relationship between bounding b…