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Sansjudge/eagle360_qwen3vl_grpo
eagle360_qwen3vl_grpo is a image-text-to-text model from Sansjudge. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.
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From the Hugging Face model README
Project page: EAGLE-360
Paper: arXiv:2607.02479
This repository contains the merged Hugging Face checkpoint used by EAGLE-360 for 360-degree panoramic object localization. Given a panoramic image and a target-object query, the model predicts the object's azimuth and elevation in degrees through multi-turn global-to-local reasoning.
The checkpoint is based on Qwen3-VL and fine-tuned with panoramic multi-turn reasoning and GRPO. It is intended to be used with the EAGLE-360 evaluation code and the panoramic Rolling RoPE patches provided in the project repository.
Public test split: Sansjudge/eagle360_test
Please install the dependencies and apply the vLLM/Transformers panoramic patches from the EAGLE-360 project repository before running evaluation.
python eval.py \
--model ./checkpoints/hf_merged \
--test_file ./eagle360_test/test.json \
--pano_dir ./eagle360_test/images \
--n_samples 50
@misc{xu2026eagle360embodiedactiveglobaltolocal,
title={EAGLE-360: Embodied Active Global-to-Local Exploration in 360$^\circ$},
author={Jingtao Xu and Zizhuo Lin and Jianwen Sun and Yi Yang and Yawei Luo},
year={2026},
eprint={2607.02479},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2607.02479},
}