The proposed MBTTBF-SCFB network achieves lower average counting error than several prior methods on ShanghaiTech, UCF_CC_50, and UCF-QNRF, though it trails CAN on two benchmarks.
A unified multi-scale deep convolutional neural network for fast object detection
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2019 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting
The proposed MBTTBF-SCFB network achieves lower average counting error than several prior methods on ShanghaiTech, UCF_CC_50, and UCF-QNRF, though it trails CAN on two benchmarks.