Crowd Counting On Ucf Cc 50
Metrics
MAE
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | MAE |
|---|---|
| locate-size-and-count-accurately-resolving | 225.6 |
| iterative-crowd-counting | 260.9 |
| multi-source-multi-scale-counting-in | 419.5 |
| encoder-decoder-based-convolutional-neural | 162.33 |
| leveraging-unlabeled-data-for-crowd-counting | 337.6 |
| segmentation-guided-attention-network-for | 224.6 |
| crowd-counting-via-adversarial-cross-scale | 291.0 |
| segmentation-guided-attention-network-for | 221.9 |
| csrnet-dilated-convolutional-neural-networks | 266.1 |
| learning-spatial-awareness-to-improve-crowd | 232.6 |
| generating-high-quality-crowd-density-maps | 295.8 |
| cross-scene-crowd-counting-via-deep | 467.0 |
| cnn-based-cascaded-multi-task-learning-of | 322.8 |
| switching-convolutional-neural-network-for | 318.1 |
| improving-point-based-crowd-counting-and | 154.8 |
| single-image-crowd-counting-via-multi-column-1 | 377.6 |
| context-aware-crowd-counting | 212.2 |
| rethinking-spatial-invariance-of-1 | 186.3 |
| scale-aggregation-network-for-accurate-and | 258.4 |
| divide-and-grow-capturing-huge-diversity-in | 291.4 |
| distribution-matching-for-crowd-counting | 211.0 |
| crowd-counting-with-deep-negative-correlation | 288.4 |