Update README.md

README.md

@@ -72,7 +72,6 @@ You can also browse the rest of our [PaGeR HF collection](https://huggingface.co
 - **Indoor / outdoor routing (inference-time add-on, not part of the paper):** The paper's per-domain numbers were produced with the indoor or outdoor scale head selected manually per dataset. For convenience in the released demo and CLI, a small zero-shot [CLIP ViT-B/32](https://github.com/openai/CLIP) classifier (loaded via [`open_clip`](https://github.com/mlfoundations/open_clip)) can auto-pick between the twin scale heads at inference time, by scoring the 4 equatorial cubemap faces against two text-prompt centroids ("indoor scene" vs. "outdoor scene"). The router lives outside the checkpoint and can be overridden by the user (`--scene_mode {auto,indoor,outdoor}`).
 - **Resolution:** Designed for high-resolution ERP inputs, up to 3K.
 - **License:** [CC BY-NC 4.0](LICENSE) — academic / non-commercial use only. The released weights are derivative works of the [Depth Anything 3](https://github.com/ByteDance-Seed/Depth-Anything-3) `da3-giant` backbone, released by ByteDance under CC BY-NC 4.0, and inherit that restriction. The CLIP ViT-B/32 weights used for the indoor/outdoor router are loaded from [`open_clip`](https://github.com/mlfoundations/open_clip) at runtime; they are MIT-licensed and travel separately, so they do not propagate any additional restriction. Commercial use is not permitted.
-- **Resources for more information:** [Project Website](https://prs-eth.github.io/PaGeR/), [Paper](https://arxiv.org/abs/2605.26368), [Code](https://github.com/prs-eth/PaGeR).
 
 ### Other released checkpoints