MonST3R PO TA S W ViTLarge BaseDecoder 512 Dpt

--- library_name: dust3r tags: - image-to-3d - model_hub_mixin - pytorch_model_hub_mixin license: cc-by-nc-sa-4.0 --- ## MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion <video controls> <source src="https://monst3r-project.github.io/files/teaser_vid_v2_lowres.mp4" type="video/mp4"> Your browser does not support the video tag. </video> ```bibtex @article{zhang2024monst3r, author = {Zhang, Junyi and Herrmann, Charles and Hur, Junhwa and Jampani, Varun and Darrell, Trevor and Cole, Forrester and Sun, Deqing and Yang, Ming-Hsuan}, title = {MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion}, journal = {arXiv preprint arxiv:2410.03825}, year = {2024} } ``` # Model info - GitHub page: https://github.com/junyi42/monst3r - Project page: https://monst3r-project.github.io/ - Paper: https://arxiv.org/abs/2410.03825 # How to use First, [install monst3r](https://github.com/junyi42/monst3r). To load the model: ```python from dust3r.model import AsymmetricCroCo3DStereo import torch model = AsymmetricCroCo3DStereo.from_pretrained("Junyi42/MonST3R_PO-TA-S-W_ViTLarge_BaseDecoder_512_dpt") device = torch.device("cuda" if torch.cuda.is_available() else "cpu") model.to(device)

Source context: 836 downloads · 22 likes · Pipeline image-to-3d · Library dust3r · Repo Junyi42/MonST3R_PO-TA-S-W_ViTLarge_BaseDecoder_512_dpt