Bo Li, Hao Zhang, Wei Dong, Peng-Tao Jiang, Jinwei Chen, Yu Liang, Longfei Huang, Lunde Chen, Wanyu Liu
We lifted 11 functions out of this paper's own repositories and ran 0 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 |
|---|---|---|
| vivoCameraResearch/SDMatte | canonical | 0 of 11 |
| Function | Status | Where it lives |
|---|---|---|
| add_aux_conv_in | Not yet run | vivoCameraResearch/SDMatte/utils/utils.py code served (permissive licence) · get_code("589373b8cfdd39d7") |
| custom_get_attention_scores | Not yet run | vivoCameraResearch/SDMatte/utils/replace.py code served (permissive licence) · get_code("44239863af5276ee") |
| custom_prepare_attention_mask | Not yet run | vivoCameraResearch/SDMatte/utils/replace.py code served (permissive licence) · get_code("07f2d45f03a56f84") |
| dgauss | Not yet run | vivoCameraResearch/SDMatte/utils/evaluate.py code served (permissive licence) · get_code("c6daa9009470dd68") |
| gauss | Not yet run | vivoCameraResearch/SDMatte/utils/evaluate.py code served (permissive licence) · get_code("b4085a9b496ef62d") |
| gauss_kernel | Not yet run | vivoCameraResearch/SDMatte/criterion.py code served (permissive licence) · get_code("b4991ebb886e5289") |
| gaussgradient | Not yet run | vivoCameraResearch/SDMatte/utils/evaluate.py code served (permissive licence) · get_code("38441a7c36e020f6") |
| get_unknown_tensor_from_pred | Not yet run | vivoCameraResearch/SDMatte/utils/utils.py code served (permissive licence) · get_code("763a4435e84627a8") |
| laplacian_loss | Not yet run | vivoCameraResearch/SDMatte/criterion.py code served (permissive licence) · get_code("a3fadbcac00e9133") |
| laplacian_pyramid | Not yet run | vivoCameraResearch/SDMatte/criterion.py code served (permissive licence) · get_code("8a0b6d481e748e9d") |
| replace_unet_conv_in | Not yet run | vivoCameraResearch/SDMatte/utils/utils.py code served (permissive licence) · get_code("91e5d642193c6016") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Figure 1. Interactive image matting results of our SDMatte with box prompts. SDMatte leverages strong diffusion priors, ensuring robust generalization. Meanwhile, it transforms the text-driven image generation capability of Stable Diffusion into a visual prompt-driven interactive capability, enabling precise alpha matte prediction based on simple user-provided visual prompts (points, boxes, masks).
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2508.00443")
get_code_for_paper("2508.00443")
have("2508.00443")
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