PPD sample output

Acknowledgement

We are grateful to the Depth Anything V2, MoGe and DiT teams for their code and model release. We would also like to sincerely thank the NeurIPS reviewers for their appreciation of this work (ratings: 5, 5, 5, 5).

Citation

If you find this project useful, please consider citing:

@article{xu2025pixel,
  title={Pixel-perfect depth with semantics-prompted diffusion transformers},
  author={Xu, Gangwei and Lin, Haotong and Luo, Hongcheng and Wang, Xianqi and Yao, Jingfeng and Zhu, Lianghui and Pu, Yuechuan and Chi, Cheng and Sun, Haiyang and Wang, Bing and others},
  journal={arXiv preprint arXiv:2510.07316},
  year={2025}
}
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