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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-to-image |
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pretty_name: REVISION_GENERATOR |
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language: |
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- en |
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--- |
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# REVISION: Rendering Tools Enable Spatial Fidelity in Vision-Language Models (ECCV 2024) |
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<img src="./misc/revision_genenator.png" width="80%" height="80%"/> |
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This is the official dataset of the REVISION framework with all the corresponding assets (i.e. objects, backgrounds, and floors). |
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## ⚒️ Requirements |
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REVISION requires [blenderproc](https://github.com/DLR-RM/BlenderProc). Simply install it with pip: |
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``` |
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pip install blenderproc |
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``` |
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## 👁️ Single Test Run |
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<img src="./misc/spatial_rel.png" width="80%" height="80%"/> |
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To generate a two-object reference image deterministically on your own, you may invoke one of the 4 blenderproc scripts in `util/`. E.g., to generate a scene of 'an **apple** *to the left* of a **banana**' in an indoor background, you may use |
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``` |
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blenderproc run util/blender_left_right_floor.py apple banana background/photo_studio_loft_hall_2k.hdr output/debug/ 0 0 |
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``` |
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The command above is equivalent for generating 'a **banana** *to the right* of an **apple**' in an indoor background. |
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## 🏃 Batched Test Run |
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We also provide ``revision_gen_sample_t2i_comp.sh`` or `` revision_gen_sample_mscoco.sh`` to synthesize a sample batch of REVISION reference images in hdf5 format. You may then visualize the reference images with: |
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``` |
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blenderproc vis hdf5 <path_to_ref_images>/<image_name>.hdf5 |
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``` |
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## 🖼️ Sample rendered outputs |
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For convenience, we also have provided rendered outputs in PNG format for all two-object-pairs in MSCOCO or those specified in T2I-CompBench. These images are also the ones used in the RevQA Benchmark. Please find out more under the folder [sample_output/](https://huggingface.co/datasets/revision-t2i/revision-generator/tree/main/sample_output) . |
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## 🤝🏼 Citation |
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```bibtex |
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@misc{chatterjee2024revisionrenderingtoolsenable, |
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title={REVISION: Rendering Tools Enable Spatial Fidelity in Vision-Language Models}, |
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author={Agneet Chatterjee and Yiran Luo and Tejas Gokhale and Yezhou Yang and Chitta Baral}, |
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year={2024}, |
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eprint={2408.02231}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2408.02231}, |
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} |
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``` |
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## 💖 Acknowledgement |
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The floor textures and the object models are sourced and modified from [sketchfab.com](https://sketchfab.com). The textured background assets are sourced from [polyhaven.com](http://polyhaven.com). All assets are shared in accordance with [CC-BY-4.0 License](https://creativecommons.org/licenses/by/4.0/deed.en#:~:text=https%3A//creativecommons.org/licenses/by/4.0/). |