We lifted 12 functions out of this paper's own repositories and ran 5 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| YoujiaZhang/Ref-GS | canonical | 5 of 12 |
| Function | Status | Where it lives |
|---|---|---|
| gaussian | Ran | YoujiaZhang/Ref-GS/utils/loss_utils.py code served (permissive licence) · get_code("c56b7ef16f309a45") |
| l1_loss | Ran | YoujiaZhang/Ref-GS/utils/loss_utils.py code served (permissive licence) · get_code("ac0e42d6fbcfbbe6") |
| l2_loss | Ran | YoujiaZhang/Ref-GS/utils/loss_utils.py code served (permissive licence) · get_code("8c3b0f873ba11813") |
| normalize_activation | Ran | YoujiaZhang/Ref-GS/lpipsPyTorch/modules/utils.py code served (permissive licence) · get_code("1dab900b2adbe38e") |
| read_next_bytes | Ran | YoujiaZhang/Ref-GS/scene/colmap_loader.py code served (permissive licence) · get_code("56858e04e6fdb2ff") |
| get_network | Not yet run | YoujiaZhang/Ref-GS/lpipsPyTorch/modules/networks.py code served (permissive licence) · get_code("07bd0da29c4dc7bb") |
| get_state_dict | Not yet run | YoujiaZhang/Ref-GS/lpipsPyTorch/modules/utils.py code served (permissive licence) · get_code("b06f27c08cf5d0ca") |
| prepare_output_and_logger | Not yet run | YoujiaZhang/Ref-GS/train-NeRF.py code served (permissive licence) · get_code("14c1f8cb24f602cf") |
| prepare_output_and_logger | Not yet run | YoujiaZhang/Ref-GS/train-NeRO.py code served (permissive licence) · get_code("c80af193336d9809") |
| prepare_output_and_logger | Not yet run | YoujiaZhang/Ref-GS/train-real.py code served (permissive licence) · get_code("495defa964436eba") |
| qvec2rotmat | Not yet run | YoujiaZhang/Ref-GS/scene/colmap_loader.py code served (permissive licence) · get_code("6ce64cf0fbcd6bb1") |
| rotmat2qvec | Not yet run | YoujiaZhang/Ref-GS/scene/colmap_loader.py code served (permissive licence) · get_code("659bc4e7e63ed8f9") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
In this paper, we introduce Ref-GS, a novel approach for directional light factorization in 2D Gaussian splatting, which enables photorealistic view-dependent appearance rendering and precise geometry recovery. Ref-GS builds upon the deferred rendering of Gaussian splatting and applies directional encoding to the deferred-rendered surface, effectively reducing the ambiguity between orientation and viewing angle. Next, we introduce a spherical Mip-grid to capture varying levels of surface roughness, enabling roughness-aware Gaussian shading. Additionally, we propose a simple yet efficient geometry-lighting factorization that connects geometry and lighting via the vector outer product, significantly reducing renderer overhead when integrating volumetric attributes. Our method achieves superior photorealistic rendering for a range of open-world scenes while also accurately recovering geometry.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2412.00905")
get_code_for_paper("2412.00905")
have("2412.00905")
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