Papers › GiT: Graph Interactive Transformer for Vehicle Re-identification
GiT: Graph Interactive Transformer for Vehicle Re-identification
Fei Shen, Yi Xie, Jianqing Zhu, Xiaobin Zhu, Huanqiang Zeng
Transformers are more and more popular in computer vision, which treat an image as a sequence of patches and learn robust global features from the sequence. However, pure transformers are not entirely suitable for vehicle re-identification because vehicle re-identification requires both robust global features and discriminative local features. For that, a graph interactive transformer (GiT) is proposed in this paper. In the macro view, a list of GiT blocks are stacked to build a vehicle re-identification model, in where graphs are to extract discriminative local features within patches and transformers are to extract robust global features among patches. In the micro view, graphs and transformers are in an interactive status, bringing effective cooperation between local and global features. Specifically, one current graph is embedded after the former level's graph and transformer, while the current transform is embedded after the current graph and the former level's transformer. In addition to the interaction between graphs and transforms, the graph is a newly-designed local correction graph, which learns discriminative local features within a patch by exploring nodes' relationships. Extensive experiments on three large-scale vehicle re-identification datasets demonstrate that our GiT method is superior to state-of-the-art vehicle re-identification approaches.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Person Re-Identification | MSMT17 | GiT | Rank-1 | 85.6 | #23 of 43 | Archive leaderboard | report |
| Person Re-Identification | MSMT17 | GiT | mAP | 64.8 | #23 of 43 | Archive leaderboard | report |
| Person Re-Identification | Market-1501 | GiT | Rank-1 | 95.7 | #45 of 135 | Archive leaderboard | report |
| Person Re-Identification | Market-1501 | GiT | mAP | 88.9 | #45 of 135 | Archive leaderboard | report |
| Vehicle Re-Identification | VeRi-776 | GiT | Rank1 | 96.86 | #12 of 17 | Archive leaderboard | report |
| Vehicle Re-Identification | VeRi-776 | GiT | mAP | 80.34 | #12 of 17 | Archive leaderboard | report |
| Vehicle Re-Identification | VehicleID Small | GiT | Rank1 | 84.65 | #11 of 13 | Archive leaderboard | report |
| Vehicle Re-Identification | VehicleID Small | GiT | mAP | 90.12 | #11 of 13 | 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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