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This model card is for the OpenLRM project, which is an open-source implementation of the paper LRM. Information contained in this model card corresponds to Version 1.1.
Fuente del modelo
Fuentes
1 fuenteVerificado 8 sept
Artefactos del modelo
2 artefactosExtractos de fuentes
2 extractosTraining data
| Model | Training Data |
|---|---|
| openlrm-obj-small-1.1 | Objaverse |
| openlrm-obj-base-1.1 | Objaverse |
| openlrm-obj-large-1.1 | Objaverse |
| openlrm-mix-small-1.1 | Objaverse + MVImgNet |
| openlrm-mix-base-1.1 | Objaverse + MVImgNet |
| openlrm-mix-large-1.1 |
Model architecture (version==1.1)
| Type | Layers | Feat. Dim | Attn. Heads | Triplane Dim. | Input Res. | Image Encoder | Size |
|---|---|---|---|---|---|---|---|
| small | 12 | 512 | 8 | 32 | 224 | dinov2_vits14_reg | 446M |
| base | 12 | 768 | 12 | 48 | 336 | dinov2_vitb14_reg |
Training settings
| Type | Rend. Res. | Rend. Patch | Ray Samples |
|---|---|---|---|
| small | 192 | 64 | 96 |
| base | 288 | 96 | 96 |
| large | 384 | 128 | 128 |
This model is an open-source implementation and is NOT the official release of the original research paper. While it aims to reproduce the original results as faithfully as possible, there may be variations due to model implementation, training data, and other factors.
This model card is subject to updates and modifications. Users are advised to check for the latest version regularly.
--- license: cc-by-nc-4.0 datasets: - allenai/objaverse pipeline_tag: image-to-3d --- # Model Card for OpenLRM V1.1 ## Overview - This model card is for the [OpenLRM](https://github.com/3DTopia/OpenLRM) project, which is an open-source implementation of the paper [LRM](https://arxiv.org/abs/2311.04400). - Information contained in this model card corresponds to [Version 1.1](https://github.com/3DTopia/OpenLRM/releases). ## Model Details - Training data | Model | Training Data | | :---: | :---: | | [openlrm-obj-small-1.1](https://huggingface.co/zxhezexin/openlrm-obj-small-1.1) | Objaverse | | [openlrm-obj-base-1.1](https://huggingface.co/zxhezexin/openlrm-obj-base-1.1) | Objaverse | | [openlrm-obj-large-1.1](https://huggingface.co/zxhezexin/openlrm-obj-large-1.1) | Objaverse | | [openlrm-mix-small-1.1](https://huggingface.co/zxhezexin/openlrm-mix-small-1.1) | Objaverse + MVImgNet | | [openlrm-mix-base-1.1](https://huggingface.co/zxhezexin/openlrm-mix-base-1.1) | Objaverse + MVImgNet | | [openlrm-mix-large-1.1](https://huggingface.co/zxhezexin/openlrm-mix-large-1.1) | Objaverse + MVImgNet | - Model architecture (version==1.1) | Type | Layers | Feat. Dim | Attn. Heads | Triplane Dim. | Input Res. | Image Encoder | Size | | :---: | :----: | :-------: | :---------: | :-----------: | :--------: | :---------------: | :---: | | small | 12 | 512 | 8 | 32 | 224 | dinov2_vits14_reg | 446M | | base | 12 | 768 | 12 | 48 | 336 | dinov2_vitb14_reg | 1.04G | | large | 16 | 1024 | 16 | 80 | 448 | dinov2_vitb14_reg | 1.81G | - Training settings | Type | Rend. Res. | Rend. Patch | Ray Samples | | :---: | :--------: | :---------: | :---------: | | small | 192 | 64 | 96 | | base | 288 | 96 | 96 | | large | 384 | 128 | 128 | ## Notable Differences from the Original Paper - We do not use the deferred back-propagation technique in the original paper. - We used random background colors during training. - The image encoder is based on the [DINOv2](https://github.com/facebookresearch/dinov2) model with register tokens. - The triplane decoder contains 4 layers in our implementation. ## License - The model weights are released under the [Creative Commons Attribution-NonCommercial 4.0 International License](LICENSE_WEIGHT). - They are provided for research purposes only, and CANNOT be used commercially. ## Disclaimer This model is an open-source implem...
Source context: 13 downloads · 2 likes · Pipeline image-to-3d · Library transformers · Repo zxhezexin/openlrm-obj-base-1.1
| Objaverse + MVImgNet |
| 1.04G |
| large | 16 | 1024 | 16 | 80 | 448 | dinov2_vitb14_reg | 1.81G |
