initial release

.gitattributes

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README.md

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+---
+license: mit
+tags:
+  - 3d-reconstruction
+  - affordance-grounding
+  - flow-matching
+  - rgbd
+arxiv: 2601.09211
+---
+
+# Affostruction
+
+**Affostruction: 3D Affordance Grounding with Generative Reconstruction** — CVPR 2026, Denver.
+
+[Chunghyun Park](https://chrockey.github.io/)<sup>1</sup>,
+[Seunghyeon Lee](https://llishyun.github.io/)<sup>1</sup>,
+[Minsu Cho](http://cvlab.postech.ac.kr/~mcho/)<sup>1,2</sup>
+
+<sup>1</sup>POSTECH &nbsp;&nbsp; <sup>2</sup>RLWRLD
+
+- Paper: https://arxiv.org/abs/2601.09211
+- Project page: https://chrockey.github.io/Affostruction/
+- Code: https://github.com/chrockey/Affostruction
+
+Pretrained checkpoints for the public release.
+
+## Reconstruction
+
+```python
+from affostruction import ReconstructionPipeline
+
+pipeline = ReconstructionPipeline.from_pretrained("chrockey/Affostruction").cuda()
+outputs = pipeline.run(input_dict)
+mesh = outputs["mesh"][0]
+gaussian = outputs["gaussian"][0]
+```
+
+Input format — see `examples/reconstruction.py` in the repo.
+
+## Affordance grounding
+
+```python
+from affostruction.pipeline import AffordancePipeline
+
+pipeline = AffordancePipeline.from_pretrained("chrockey/Affostruction")
+# NOTE: pipeline.run() is not yet wired in the release package.
+# Downloads + parses the checkpoint; full inference requires ElasticSLatFlowModel
+# to be registered in affostruction/models/.
+```

affordance/config.json

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+{
+  "denoiser": {
+    "name": "ElasticSLatFlowModel",
+    "args": {
+      "resolution": 64,
+      "in_channels": 1,
+      "out_channels": 1,
+      "model_channels": 768,
+      "cond_channels": 768,
+      "num_blocks": 12,
+      "num_heads": 12,
+      "mlp_ratio": 4,
+      "patch_size": 2,
+      "num_io_res_blocks": 2,
+      "io_block_channels": [
+        128
+      ],
+      "pe_mode": "ape",
+      "qk_rms_norm": true,
+      "use_fp16": true
+    }
+  },
+  "text_cond_model": "openai/clip-vit-large-patch14"
+}

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reconstruction/config.json

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+{
+  "denoiser": {
+    "name": "SparseStructureFlowModel",
+    "args": {
+      "resolution": 16,
+      "in_channels": 8,
+      "out_channels": 8,
+      "model_channels": 768,
+      "cond_channels": 1024,
+      "num_blocks": 12,
+      "num_heads": 12,
+      "mlp_ratio": 4,
+      "patch_size": 1,
+      "pe_mode": "ape",
+      "qk_rms_norm": true,
+      "use_fp16": true
+    }
+  },
+  "voxel_resolution": 16,
+  "image_size": 224,
+  "dinov2_model": "dinov2_vitl14_reg"
+}

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