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MODEL_ZOO.md

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+# 🫧 Model Zoo

README.md

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+---
+license: cc-by-4.0
+tags:
+- 3d-reconstruction
+- gaussian-splatting
+- learned-optimizer
+- computer-vision
+- view-synthesis
+- pytorch
+---
+
+# 🫧 Learn2Splat: Learned Optimizer for 3D Gaussian Splatting
+
+**Learn2Splat** is a meta-learned optimizer for **3D Gaussian Splatting
+(3DGS)** that replaces hand-designed optimizers (e.g., Adam/SGD) with a
+learned update rule.
+
+It improves early convergence speed while remaining stable over long
+optimization horizons---without requiring learning-rate schedules or
+time-step conditioning.
+
+------------------------------------------------------------------------
+
+## 🌐 Links
+
+-   Project page: https://naamapearl.github.io/learn2splat/
+-   Code: https://github.com/autonomousvision/learn2splat
+-   Hugging Face: https://huggingface.co/autonomousvision/learn2splat
+
+------------------------------------------------------------------------
+
+## ⚙️ Overview
+
+Learn2Splat learns to optimize Gaussian scene representations by
+directly predicting structured parameter updates.
+
+Key properties:
+
+-   Learned optimizer for 3D Gaussian Splatting
+-   Faster early convergence compared to standard optimizers
+-   Stable long-horizon optimization without LR schedules
+-   Zero-shot generalization to unseen scenes and resolutions
+
+The model is trained across many scenes and applied without fine-tuning
+at test time.
+
+------------------------------------------------------------------------
+
+## 📦 Checkpoints
+
+This repository includes pretrained weights for:
+
+-   Learn2SplatSparse: sparse-view reconstruction
+-   Learn2SplatDense: dense-view reconstruction
+
+See MODEL_ZOO.md for details.
+
+------------------------------------------------------------------------
+
+## 🚀 Usage
+
+from transformers import AutoModel
+
+model_id = "autonomousvision/learn2splat"
+
+model = AutoModel.from_pretrained(model_id, trust_remote_code=True)
+model.eval()
+
+------------------------------------------------------------------------
+
+## 📚 Citation
+
+@article{pearl2026learn2splat, title={Learn2Splat: Extending the Horizon
+of Learned 3DGS Optimization}, author={Pearl, Naama and Esposito,
+Stefano and Xu, Haofei and Peleg, Amit and Gschossmann, Patricia and
+Porzi, Lorenzo and Kontschieder, Peter and Pons-Moll, Gerard and Geiger,
+Andreas}, journal={arXiv preprint}, year={2026} }