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Running on Zero
| title: CodecSplat | |
| emoji: 🗜️ | |
| colorFrom: red | |
| colorTo: yellow | |
| sdk: gradio | |
| sdk_version: 6.30.0 | |
| app_file: app.py | |
| short_description: Compress a 3D Gaussian scene into a few KB | |
| python_version: "3.12" | |
| startup_duration_timeout: 1h | |
| models: | |
| - pengpeng-yu/CodecSplat | |
| # CodecSplat: Ultra-Compact Latent Coding for Feed-Forward 3D Gaussian Splatting | |
| Interactive demo of [CodecSplat](https://huggingface.co/papers/2605.25563) | |
| ([code](https://github.com/pengpeng-yu/CodecSplat), MIT; | |
| [weights](https://huggingface.co/pengpeng-yu/CodecSplat)). | |
| Upload overlapping photos of a static scene. The Space: | |
| 1. runs **COLMAP** (`pycolmap`, CPU) to estimate intrinsics and camera poses, | |
| 2. picks 8 context views by farthest-point sampling and resizes them to 256x448 | |
| (the `codecsplat-base-dl3dv-256x448-view8` checkpoint), | |
| 3. runs the authors' **complete bitstream path** (`EncoderCodecSplat.codec_forward`): | |
| it encodes the latent features into a real entropy-coded scene bitstream at the | |
| chosen rate point λ (16-1024), then decodes that bitstream back to 3D Gaussians, | |
| 4. renders held-out views (with PSNR/SSIM against the real photos) and a | |
| fly-through with `gsplat`, and shows the Gaussians in an interactive viewer. | |
| You can download both the `.bin` bitstream and the decoded `.ply`. | |
| ## Implementation notes | |
| * Model construction uses the exact Hydra overrides of the authors' | |
| `scripts/test_dl3dv_view8_256x448.sh` (bf16 autocast, gsplat antialiased rasterizer). | |
| * COLMAP stage and scene loader are adapted from the | |
| [ReSplat Space](https://huggingface.co/spaces/hugging-apps/resplat-recurrent-gs) / the ReSplat | |
| reference `scripts/infer_colmap.py` (same DepthSplat camera conventions). The reconstruction is | |
| normalised to a fixed extent so that the DL3DV near/far planes (0.5 / 200) are meaningful. | |
| * `gsplat`'s CUDA kernels are JIT-compiled once at startup (no prebuilt sm_120 wheel). | |
| ## Example assets | |
| `examples/kitchen` and `examples/garden` are 14 frames each from the | |
| [Mip-NeRF 360](https://jonbarron.info/mipnerf360/) dataset (Barron et al.), downscaled to 960px, | |
| as redistributed by [`nvs-bench/mipnerf360`](https://huggingface.co/datasets/nvs-bench/mipnerf360) (MIT). | |