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README.md
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## Method
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<p align="center">
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<img src="https://lhmd.top/trisplat/assets/pipeline2.png" alt="TriSplat pipeline" width="100%">
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</p>
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Given sparse input views, TriSplat predicts dense local point maps, triangle attributes, camera poses, and optional intrinsics. Point-map geometry anchors triangle orientation through geometry normals, a learned normal refiner, and a monocular-normal bootstrap. A differentiable triangle rasterizer renders RGB, depth, and normals, while mesh export only needs opacity filtering, winding correction, and duplicate-vertex merging.
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## Method
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<p align="center">
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<img src="https://lhmd.top/trisplat/assets/images/pipeline2.png" alt="TriSplat pipeline" width="100%">
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</p>
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Given sparse input views, TriSplat predicts dense local point maps, triangle attributes, camera poses, and optional intrinsics. Point-map geometry anchors triangle orientation through geometry normals, a learned normal refiner, and a monocular-normal bootstrap. A differentiable triangle rasterizer renders RGB, depth, and normals, while mesh export only needs opacity filtering, winding correction, and duplicate-vertex merging.
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