princeton-vl/WMGStereo
What Makes Good Synthetic Training Data for Zero-Shot Stereo Matching? (WMGStereo) Paper | GitHub WMGStereo is a procedural dataset generator specifically optimized for zero-shot stereo matching performance. This repository contains the WMGStereo-150k dataset, a large-scale synthetic training dataset featuring indoor, nature, and dense "flying" scenes. Dataset Download You can download the dataset using the huggingface-cli: pip install huggingface-cli… See the full description on the dataset page: https://huggingface.co/datasets/princeton-vl/WMGStereo.
| Author / organization | princeton-vl |
|---|---|
| License (as declared) | bsd-3-clause |
| Downloads | 2.2K (as reported by Hugging Face) |
| Likes | 6 |
| Created | 26 June 2025 |
| Last updated at source | 4 March 2026 |
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- 17 Oct 2026 Description: What Makes Good Synthetic Training Data for Zero-Shot Stereo Matching? (WMGStereo) Paper | GitHub WMGStereo is a procedural dataset generator specifically optimized for zero-shot stereo matching performance. This repository contains the WMG → What Makes Good Synthetic Training Data for Zero-Shot Stereo Matching? (WMGStereo) Paper | GitHub WMGStereo is a procedural dataset generator specifically optimized for zero-shot stereo matching performance. This repository contains the WMG
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