| --- |
| license: cc-by-nc-sa-4.0 |
| library_name: pytorch |
| language: |
| - en |
| tags: |
| - ditgs |
| - 3d-reconstruction |
| - gaussian-splatting |
| - multiview |
| base_model: |
| - Wan-AI/Wan2.2-TI2V-5B-Diffusers |
| - nightkiller/FlashWorldPretrain |
| - jiaweir/tokengs |
| base_model_relation: finetune |
| --- |
| # DiTGS |
|
|
| Camera-fixed Residual Cross-Attention feature readout for 3D Gaussian reconstruction. |
|
|
| [Code, installation and training](https://github.com/Qingzhongyun/DiTGS) |
|
|
| ## Checkpoint |
|
|
| `model.pt` is the **raw final main-model checkpoint after 10,000 warmup updates |
| and 20,000 additional joint updates**. It uses the corrected-camera pipeline. |
| It is not an EMA checkpoint or an attention-ablation checkpoint. |
|
|
| The file is approximately 22.055 GB in decimal units. It contains the complete |
| inference network: the fine-tuned FlashWorld/Wan transformer, frozen Wan VAE, |
| frozen TokenGS image encoder, fine-tuned GS decoder/head, new adapter, independent |
| DiT-memory attention/KV/LayerScale branches, cached empty prompt and all required |
| normalization/rotary buffers. Storage dtypes and tensor values are unchanged. |
| There is no optimizer, EMA, RNG state, dataset media or full UMT5 text encoder. |
| Original server paths have been replaced with portable relative configuration. |
| `release.json` records the exact size, SHA256, component sizes and model contract. |
|
|
| ## Download and inference |
|
|
| Install the source repository's pinned dependencies first. This is a custom |
| PyTorch model; it is not a Diffusers `from_pretrained` pipeline. |
|
|
| ```bash |
| hf download qyk21/DiTGS --local-dir weights/ditgs |
| bash scripts/infer.sh 1 --checkpoint weights/ditgs/model.pt --data-root /path/to/DL3DV/benchmark --output outputs/residual/dl3dv_1view |
| bash scripts/infer.sh 2 --checkpoint weights/ditgs/model.pt --data-root /path/to/DL3DV/benchmark --output outputs/residual/dl3dv_2view |
| ``` |
|
|
| Run commands from the DiTGS code repository. The full checkpoint includes the |
| pretrained components needed for model inference; separate Wan/FlashWorld/TokenGS |
| weight downloads are required for training from initialization, not for loading |
| this file. LPIPS/VGG evaluation weights are downloaded separately by their |
| libraries. Use a CUDA GPU with enough memory for the complete model and rendering; |
| this publication did not establish a minimum GPU-memory requirement. |
|
|
| The benchmark expects posed images and camera intrinsics/extrinsics, not unposed |
| image reconstruction. The released 2-view index contains 140 scenes and 50 target |
| frames per scene. The 1-view setting uses its first context frame. Training used |
| 2 input views. Default inference uses all 8 DiT camera slots, Euler NFE=1, |
| seed=42, native 256x448 evaluation, and no test-time optimization. |
| See the source README for novel-target versus input-overlap scoring and ZIP layout. |
|
|
| ## License and upstream attribution |
|
|
| The checkpoint is released under **CC BY-NC-SA 4.0** in inheritance of the |
| FlashWorld pretrained-weight terms, with the upstream notices retained. |
| It is intended for **noncommercial academic research**. Retain attribution, |
| identify modifications and comply with ShareAlike when distributing adaptations. |
| The code repository's Apache-2.0 license is separate from this weight release. |
|
|
| TokenGS's root release README states Apache-2.0, while its separate model card |
| at the same upstream revision names a restrictive NVIDIA internal-research |
| license. This release follows the root release declaration; the discrepancy is |
| preserved explicitly in [UPSTREAM_NOTICES.md](UPSTREAM_NOTICES.md), including |
| links to both statements. No separate written upstream clarification is claimed. |
| A research-use statement does not override applicable upstream restrictions. |
| See [LICENSE](LICENSE), [NOTICE](NOTICE) and [UPSTREAM_NOTICES.md](UPSTREAM_NOTICES.md). |
|
|
| Please cite and acknowledge TokenGS, FlashWorld, Wan and DL3DV in work using this |
| model. Original paper/project links and changes are recorded in NOTICE. |
|
|
| ## Validation and limitations |
|
|
| Packaging used CPU serialization only. Every model tensor and buffer was compared |
| with the existing inference export and found identical; the model contract was |
| also preserved. No CUDA training, inference, speed or quality evaluation was rerun |
| for this upload. No new performance claims are made here. This checkpoint is for |
| the main Residual CA model; ablation training scripts are in the code repository. |
|
|
