17 citations · 24 across the 5 of their papers we have counts for
5 papers
PolarMOT: How Far Can Geometric Relations Take Us in 3D Multi-Object Tracking?
Aleksandr Kim, Guillem Brasó, Aljoša Ošep +1
Most (3D) multi-object tracking methods rely on appearance-based cues for data association. By contrast, we investigate how far we can get by only encoding geometric relationships…
DeVIS: Making Deformable Transformers Work for Video Instance Segmentation
Adrià Caelles, Tim Meinhardt, Guillem Brasó +1
Video Instance Segmentation (VIS) jointly tackles multi-object detection, tracking, and segmentation in video sequences. In the past, VIS methods mirrored the fragmentation of thes…
HOLISMOKES -- IX. Neural network inference of strong-lens parameters and uncertainties from ground-based images
S. Schuldt, R. Cañameras, Y. Shu +4
Modeling of strong gravitational lenses is a necessity for further applications in astrophysics and cosmology. Especially with the large number of detections in current and upcomin…
A Unified Framework for Implicit Sinkhorn Differentiation
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé +2
The Sinkhorn operator has recently experienced a surge of popularity in computer vision and related fields. One major reason is its ease of integration into deep learning framework…
Forecasting from LiDAR via Future Object Detection
Neehar Peri, Jonathon Luiten, Mengtian Li +3
Object detection and forecasting are fundamental components of embodied perception. These two problems, however, are largely studied in isolation by the community. In this paper, w…