Papers › Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework
Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework
Seoik Jung, Taekyung Song
In this paper, we investigate the applicability of the CLIP-EBC framework, originally designed for crowd counting, to car object counting using the CARPK dataset. Experimental results show that our model achieves second-best performance compared to existing methods. In addition, we propose a K-means weighted clustering method to estimate object positions based on predicted density maps, indicating the framework's potential extension to localization tasks.
Code
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Object Counting | CARPK | CLIP-LOCAR | MAE | 4.01 | #2 of 15 | Archive leaderboard | report |
| Object Counting | CARPK | CLIP-LOCAR | RMSE | 6.02 | #2 of 15 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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