| EBC-ZIP-B |
- MAE
- 5.51
- RMSE
- 8.63
|
EBC-ZIP: Improving Blockwise Crowd Counting with Zero-Inflated Poisson Regression 2025-06-24 |
코드 1 |
| PSL-Net |
- MAE
- 5.8
- RMSE
- 9.2
|
Crowd Counting and Individual Localization Using Pseudo Square Label 2024-05-13 |
연결 없음 |
| CLIP-EBC (ViT-L/14) |
- MAE
- 5.9
- RMSE
- 9.2
|
CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification 2024-03-14 |
코드 1 |
| CLIP-EBC (ResNet50) |
- MAE
- 6.0
- RMSE
- 10.1
|
CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification 2024-03-14 |
코드 1 |
| GauNet (ResNet-50) |
- MAE
- 6.0
|
Rethinking Spatial Invariance of Convolutional Networks for Object Counting 2022-06-10 |
코드 1 |
| SGANet |
- MAE
- 6.3
|
Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss 2019-11-18 |
코드 1 |
| M-SFANet+M-SegNet |
- MAE
- 6.32
- MSE
- 10.06
|
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting 2020-03-12 |
코드 1 · 코드 2 |
| SPANet |
- MAE
- 6.5
|
Learning Spatial Awareness to Improve Crowd Counting 2019-09-16 |
연결 없음 |
| CLIP-EBC (ViT-B/16) |
- MAE
- 6.6
- RMSE
- 10.5
|
CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification 2024-03-14 |
코드 1 |
| SGANet + CL |
- MAE
- 6.6
|
Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss 2019-11-18 |
코드 1 |
| S-DCNet |
- MAE
- 6.7
|
From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer 2019-08-15 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| FusionCount |
- MAE
- 6.9
- MSE
- 11.8
|
FusionCount: Efficient Crowd Counting via Multiscale Feature Fusion 2022-02-28 |
코드 1 |
| CSRNet-EBC |
- MAE
- 6.9
- RMSE
- 11.3
|
CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification 2024-03-14 |
코드 1 |
| DMCount-EBC |
- MAE
- 7.0
- RMSE
- 10.9
|
CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification 2024-03-14 |
코드 1 |
| DM-Count |
- MAE
- 7.4
|
Distribution Matching for Crowd Counting 2020-09-28 |
코드 1 |
| CAN |
- MAE
- 7.8
|
Context-Aware Crowd Counting 2018-11-26 |
코드 1 · 코드 2 · 코드 3 |
| LSC-CNN |
- MAE
- 8.1
|
Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection 2019-06-18 |
코드 1 · 코드 2 |
| SANet |
- MAE
- 8.4
|
Scale Aggregation Network for Accurate and Efficient Crowd Counting 2018-09-01 |
코드 1 |
| APGCC |
- MAE
- 8.7
|
Improving Point-based Crowd Counting and Localization Based on Auxiliary Point Guidance 2024-05-17 |
코드 1 |
| OrdinalEntropy |
- MAE
- 9.1
- MSE
- 14.5
|
Improving Deep Regression with Ordinal Entropy 2023-01-21 |
코드 1 |
| SAFECount |
- MAE
- 9.98
|
Few-shot Object Counting with Similarity-Aware Feature Enhancement 2022-01-22 |
코드 1 |
| CSRNet |
- MAE
- 10.6
|
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes 2018-02-27 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 |
| ic-CNN |
- MAE
- 10.7
|
Iterative Crowd Counting 2018-07-26 |
연결 없음 |
| IG-CNN |
- MAE
- 13.6
|
Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN 2018-07-26 |
연결 없음 |
| Liu et al. |
- MAE
- 13.7
|
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank 2018-03-08 |
코드 1 |
| ACSCP |
- MAE
- 17.2
|
Crowd Counting via Adversarial Cross-Scale Consistency Pursuit 2018-06-01 |
코드 1 |
| D-ConvNet |
- MAE
- 18.7
|
Crowd Counting With Deep Negative Correlation Learning 2018-06-01 |
코드 1 |
| Cascaded-MTL |
- MAE
- 20
|
CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting 2017-07-30 |
코드 1 |
| CP-CNN |
- MAE
- 20.1
|
Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs 2017-08-02 |
연결 없음 |
| Switch-CNN |
- MAE
- 21.6
|
Switching Convolutional Neural Network for Crowd Counting 2017-08-01 |
코드 1 |