Instructions to use FudanCVL/OcclusionFormer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FudanCVL/OcclusionFormer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FudanCVL/OcclusionFormer", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update model card metadata, links and usage instructions
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by nielsr HF Staff - opened
README.md
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---
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library_name: diffusers
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pipeline_tag: text-to-image
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tags:
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- occlusion
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- layout
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- flux
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language:
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---
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<table align="center" cellspacing="0" cellpadding="0" style="margin:0 auto;">
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<tr>
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<td valign="middle" style="padding-right:10px;">
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<div align="center" style="margin-top:14px;">
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<a href='https://henghuiding.com/OcclusionFormer/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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<a href='https://icml.cc/
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<a href='https://arxiv.org/'><img src='https://img.shields.io/badge/arXiv-
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<a href='https://huggingface.co/'><img src='https://img.shields.io/badge/%F0%9F%A4%97%
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<a href='https://huggingface.co/datasets/FudanCVL/SA-Z'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20SA--Z-Hugging Face%20-orange'></a>
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</div>
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<p align="center" style="margin:4px 0 0 0;">
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<p align="center" style="margin:1px 0 0 0; font-size:1.48em; font-weight:900; color:#ff6a00;">ICML 2026</p>
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<p align="center" style="margin:1px 0 0 0; font-size:1.08em; color:#6b7280;"><em>✉ Corresponding Author</em></p>
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## 🔥 News
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- [2026/05/18] Release **inference code**, **model weights** and **SA-Z dataset**.
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- [2026/05/18] Release **OcclusionFormer open-source package** in this repository.
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- [2026/4/30] OcclusionFormer is accepted to **ICML 2026**.
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3. Download checkpoint
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```
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https://huggingface.co/FudanCVL/OcclusionFormer
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```
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4. Run Streamlit demo
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--overwrite
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```
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Batch inference with a directory of JSON layouts:
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```bash
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python inference_occlusionformer.py \
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--model_path /path/to/FLUX.1-dev \
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--ckpt_path /path/to/occlusionformer_checkpoint_dir \
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--layout_dir ./examples \
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--output_dir ./outputs_occlusionformer \
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--enable_layout \
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--overwrite
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```
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---
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## ✅ TODO
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---
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language:
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- en
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library_name: diffusers
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license: mit
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pipeline_tag: text-to-image
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base_model: black-forest-labs/FLUX.1-dev
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datasets:
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- FudanCVL/SA-Z
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tags:
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- occlusion
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- layout
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- flux
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<table align="center" cellspacing="0" cellpadding="0" style="margin:0 auto;">
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<tr>
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<td valign="middle" style="padding-right:10px;">
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<div align="center" style="margin-top:14px;">
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<a href='https://henghuiding.com/OcclusionFormer/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
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<a href='https://icml.cc/virtual/2026/poster/66159'><img src='https://img.shields.io/badge/ICML-2026-blue'></a>
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<a href='https://arxiv.org/abs/2605.21343'><img src='https://img.shields.io/badge/arXiv-2605.21343-b31b1b.svg'></a>
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<a href='https://huggingface.co/papers/2605.21343'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Paper-Hugging Face-orange'></a>
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<a href='https://huggingface.co/datasets/FudanCVL/SA-Z'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20SA--Z-Hugging Face%20-orange'></a>
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</div>
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<p align="center" style="margin:4px 0 0 0;">
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<p align="center" style="margin:1px 0 0 0; font-size:1.48em; font-weight:900; color:#ff6a00;">ICML 2026</p>
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<p align="center" style="margin:1px 0 0 0; font-size:1.08em; color:#6b7280;"><em>✉ Corresponding Author</em></p>
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This repository contains the weights for **OcclusionFormer**, as presented in the paper [OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation](https://huggingface.co/papers/2605.21343).
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The official code is available at: [https://github.com/FudanCVL/OcclusionFormer](https://github.com/FudanCVL/OcclusionFormer)
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## 🔥 News
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- [2026/05/21] Release **OcclusionFormer** on [ArXiv](https://arxiv.org/abs/2605.21343)!
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- [2026/05/18] Release **inference code**, **model weights** and **SA-Z dataset**.
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- [2026/05/18] Release **OcclusionFormer open-source package** in this repository.
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- [2026/4/30] OcclusionFormer is accepted to **ICML 2026**.
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3. Download checkpoint
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Weights can be found in this repository. Download `occlusionformer` to `./ckpt`.
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4. Run Streamlit demo
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--overwrite
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```
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---
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## ✅ TODO
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