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ImAge4VPR
fenglu96/ImAge4VPR
ImAge4VPR is a machine learning model from fenglu96. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
ImAge is an implicit aggregation method to get robust global image descriptors for visual place recognition, which neither modifies the backbone nor needs an extra aggregator. This work outperforms previous SOTA metho…
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Updated Feb 2, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Feb 1, 2026
- Updated
- Feb 2, 2026
- SHA
- f3866fc9
Model card
From the Hugging Face model README
ImAge
ImAge is an implicit aggregation method to get robust global image descriptors for visual place recognition, which neither modifies the backbone nor needs an extra aggregator. This work outperforms previous SOTA methods on several VPR benchmarks.
Paper: Towards Implicit Aggregation: Robust Image Representation for Place Recognition in the Transformer Era (NeurIPS 2025)
GitHub: Lu-Feng/ImAge
Usage
import torch
model = torch.hub.load("Lu-Feng/ImAge", "ImAge")
model.eval()
# Extract descriptor from an image
image = torch.randn(1, 3, 322, 322) # [B, 3, H, W]
with torch.no_grad():
descriptor = model(image) # [B, 6144] L2-normalized descriptor
Citation
@inproceedings{ImAge,
title={Towards Implicit Aggregation: Robust Image Representation for Place Recognition in the Transformer Era},
author={Feng Lu and Tong Jin and Canming Ye and Xiangyuan Lan and Yunpeng Liu and Chun Yuan},
booktitle={The Annual Conference on Neural Information Processing Systems},
year={2025}
}
- License
- mit
- Created
- Feb 1, 2026
- Updated
- Feb 2, 2026