Papers › CounTR: Transformer-based Generalised Visual Counting
CounTR: Transformer-based Generalised Visual Counting
Chang Liu, Yujie Zhong, Andrew Zisserman, Weidi Xie
In this paper, we consider the problem of generalised visual object counting, with the goal of developing a computational model for counting the number of objects from arbitrary semantic categories, using arbitrary number of "exemplars", i.e. zero-shot or few-shot counting. To this end, we make the following four contributions: (1) We introduce a novel transformer-based architecture for generalised visual object counting, termed as Counting Transformer (CounTR), which explicitly capture the similarity between image patches or with given "exemplars" with the attention mechanism;(2) We adopt a two-stage training regime, that first pre-trains the model with self-supervised learning, and followed by supervised fine-tuning;(3) We propose a simple, scalable pipeline for synthesizing training images with a large number of instances or that from different semantic categories, explicitly forcing the model to make use of the given "exemplars";(4) We conduct thorough ablation studies on the large-scale counting benchmark, e.g. FSC-147, and demonstrate state-of-the-art performance on both zero and few-shot settings.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Exemplar-Free Counting | FSC147 | CounTR | MAE(test) | 14.71 | #4 of 9 | Archive leaderboard | report |
| Exemplar-Free Counting | FSC147 | CounTR | MAE(val) | 18.07 | #4 of 9 | Archive leaderboard | report |
| Exemplar-Free Counting | FSC147 | CounTR | RMSE(test) | 106.87 | #4 of 9 | Archive leaderboard | report |
| Exemplar-Free Counting | FSC147 | CounTR | RMSE(val) | 71.84 | #4 of 9 | Archive leaderboard | report |
| Object Counting | CARPK | CounTR | MAE | 5.75 | #4 of 15 | Archive leaderboard | report |
| Object Counting | CARPK | CounTR | RMSE | 7.45 | #4 of 15 | Archive leaderboard | report |
| Object Counting | FSC147 | CounTR | MAE(test) | 11.95 | #8 of 19 | Archive leaderboard | report |
| Object Counting | FSC147 | CounTR | MAE(val) | 13.13 | #8 of 19 | Archive leaderboard | report |
| Object Counting | FSC147 | CounTR | RMSE(test) | 91.23 | #8 of 19 | Archive leaderboard | report |
| Object Counting | FSC147 | CounTR | RMSE(val) | 49.83 | #8 of 19 | 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.
Methods
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