297 citations · 601 across the 19 of their papers we have counts for
6 papers · 1 filter
Siam R-CNN: Visual Tracking by Re-Detection
Paul Voigtlaender, Jonathon Luiten, Philip H. S. Torr +1
We present Siam R-CNN, a Siamese re-detection architecture which unleashes the full power of two-stage object detection approaches for visual object tracking. We combine this with…
Large-Scale Object Mining for Object Discovery from Unlabeled Video
Aljosa Osep, Paul Voigtlaender, Jonathon Luiten +2
This paper addresses the problem of object discovery from unlabeled driving videos captured in a realistic automotive setting. Identifying recurring object categories in such raw v…
BoLTVOS: Box-Level Tracking for Video Object Segmentation
Paul Voigtlaender, Jonathon Luiten, Bastian Leibe
We approach video object segmentation (VOS) by splitting the task into two sub-tasks: bounding box level tracking, followed by bounding box segmentation. Following this paradigm, w…
FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation
Paul Voigtlaender, Yuning Chai, Florian Schroff +3
Many of the recent successful methods for video object segmentation (VOS) are overly complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of…
MOTS: Multi-Object Tracking and Segmentation
Paul Voigtlaender, Michael Krause, Aljosa Osep +4
This paper extends the popular task of multi-object tracking to multi-object tracking and segmentation (MOTS). Towards this goal, we create dense pixel-level annotations for two ex…
4D Generic Video Object Proposals
Aljosa Osep, Paul Voigtlaender, Mark Weber +2
Many high-level video understanding methods require input in the form of object proposals. Currently, such proposals are predominantly generated with the help of networks that were…