M-SFANet+M-SegNet

Reported on 5 benchmarks across 1 task · 1 paper · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision5 results

CrowdsonShanghaiTech B
MSE· uses extra data· 2020-03-12
10.06
SOTA
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting arXiv:2003.05586
CrowdsonTRANCOS
MAE· 2020-03-12
2.22
SOTA
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting arXiv:2003.05586
CrowdsonShanghaiTech A
MAE· 2020-03-12
57.55
best: 47.81 (EBC-ZIP-B)
SOTA
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting arXiv:2003.05586
CrowdsonShanghaiTech B
MAE· uses extra data· 2020-03-12
6.32
best: 5.51 (EBC-ZIP-B)
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting arXiv:2003.05586
CrowdsonShanghaiTech A
MSE· 2020-03-12
94.48
best: 76.7 (APGCC)
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting arXiv:2003.05586