Michael Black, Hongwei Yi, Shashank Tripathi, Dimitrios Tzionas, Agniv Chatterjee, Jean-Claude Passy
We lifted 12 functions out of this paper's own repositories and ran 7 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 |
|---|---|---|
| sha2nkt/deco | — | 7 of 12 |
| Function | Status | Where it lives |
|---|---|---|
| BasicBlock | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("aa08b1e9b931f4dd") |
| Classifier | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("4c099b4d3a311a6f") |
| Cross_Att | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("3fc2ad51ca7a1405") |
| Decoder | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("5f277424861d148f") |
| HighResolutionModule | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("a06fe498ccd35dab") |
| Self_Attn | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("80c771b3b438e460") |
| get_cfg_defaults | Ran | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("779c0baa2f2d2439") |
| DECO | Not yet run | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("df75e7818b4fed38") |
| Encoder | Not yet run | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("0d8376e8bee064b3") |
| PoseHighResolutionNet | Not yet run | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("6fb96a9d4d5b6696") |
| get_pose_net | Not yet run | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("8c72b232bd94f8d4") |
| hrnet_w32 | Not yet run | sha2nkt/deco/models/deco.py pointer only (licence: NOASSERTION) · get_code("5e2070c53b6e1fcb") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Figure 1: Given an RGB image, DECO infers dense vertex-level 3D contacts on the full human body. To this end, it reasons about the contacting body parts, human-object proximity, and the surrounding scene context to infer 3D contact for diverse human-object and human-scene interactions. Blue areas show the inferred contact on the body, hands, and feet for each image.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2309.15273")
get_code_for_paper("2309.15273")
have("2309.15273")
Connect an agent — have() is free.