Add model card and metadata

README.md

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-license: mit
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+---
+license: mit
+pipeline_tag: image-feature-extraction
+---
+
+# UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer
+
+UniPR-3D is a universal visual place recognition (VPR) framework that effectively integrates information from multiple views. It supports both frame-to-frame and sequence-to-sequence matching by leveraging 3D and 2D tokens with tailored aggregation strategies.
+
+- **Paper:** [UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer](https://huggingface.co/papers/2512.21078)
+- **Repository:** [https://github.com/dtc111111/UniPR-3D](https://github.com/dtc111111/UniPR-3D)
+
+## Description
+UniPR-3D builds on a Visual Geometry Grounded Transformer (VGGT) backbone capable of encoding multi-view 3D representations. To construct its descriptor, the model jointly leverages 3D tokens and intermediate 2D tokens, using dedicated aggregation modules to capture fine-grained texture cues while reasoning across viewpoints. To further enhance generalization, it incorporates both single- and multi-frame aggregation schemes along with a variable-length sequence retrieval strategy. It achieves state-of-the-art performance on several benchmarks, including MSLS, Pittsburgh, NordLand, and SPED.
+
+## Citation
+
+If you find our paper and code useful, please cite us:
+
+```bibtex
+@inproceedings{deng2026_unipr3d,
+  title     = {UniPR-3D: Towards Universal Visual Place Recognition with 3D Visual Geometry Grounded Transformer},
+  author    = {Tianchen Deng and Xun Chen and Ziming Li and Hongming Shen and Danwei Wang and Javier Civera and Hesheng Wang},
+  booktitle = {Arxiv},
+  year      = {2026},
+}
+```