25 citations · 26 across the 2 of their papers we have counts for
2 papers
cs.CV2018★ 25 cited
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation
Radek Mackowiak, Philip Lenz, Omair Ghori +3
State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images. However, gathering such a corpus…
cs.CV2014★ 1 cited
FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation
Philip Lenz, Andreas Geiger, Raquel Urtasun
One of the most popular approaches to multi-target tracking is tracking-by-detection. Current min-cost flow algorithms which solve the data association problem optimally have three…