Papers › NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination
NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination
Penghao Zhou, Chong Zhou, Pai Peng, Junlong Du, Xing Sun, Xiaowei Guo, Feiyue Huang
Greedy-NMS inherently raises a dilemma, where a lower NMS threshold will potentially lead to a lower recall rate and a higher threshold introduces more false positives. This problem is more severe in pedestrian detection because the instance density varies more intensively. However, previous works on NMS don't consider or vaguely consider the factor of the existent of nearby pedestrians. Thus, we propose Nearby Objects Hallucinator (NOH), which pinpoints the objects nearby each proposal with a Gaussian distribution, together with NOH-NMS, which dynamically eases the suppression for the space that might contain other objects with a high likelihood. Compared to Greedy-NMS, our method, as the state-of-the-art, improves by 3.9% AP, 5.1% Recall, and 0.8% MR⁻² on CrowdHuman to 89.0% AP and 92.9% Recall, and 43.9% MR⁻² respectively.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Object Detection | CrowdHuman (full body) | NOH-NMS | AP | 89.0 | #13 of 19 | Archive leaderboard | report |
| Object Detection | CrowdHuman (full body) | NOH-NMS | mMR | 43.9 | #13 of 19 | Archive leaderboard | report |
| Pedestrian Detection | CityPersons | NOH-NMS | Bare MR^-2 | 6.6 | #13 of 22 | Archive leaderboard | report |
| Pedestrian Detection | CityPersons | NOH-NMS | Heavy MR^-2 | 53.0 | #13 of 22 | Archive leaderboard | report |
| Pedestrian Detection | CityPersons | NOH-NMS | Partial MR^-2 | 11.2 | #13 of 22 | Archive leaderboard | report |
| Pedestrian Detection | CityPersons | NOH-NMS | Reasonable MR^-2 | 10.8 | #13 of 22 | 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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