Methods › General › Interpretability › Hierarchical Network Dissection
Hierarchical Network Dissection
Introduced by Divyang Teotia et al. in Interpreting Face Inference Models using Hierarchical Network Dissection
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Hierarchical Network Dissection is a pipeline for interpreting the internal representation of face-centric inference models. Using a probabilistic formulation, Hierarchical Network Dissection pairs units of the model with concepts in a "Face Dictionary" (a collection of facial concepts with corresponding sample images). Interpretable units are discovered in a convolution layer through HND to identify multiple instances of unit-concept affinity. The pipeline is inspired by Network Dissection, an interpretability model for object-centric and scene-centric models.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
Interpreting Face Inference Models using Hierarchical Network Dissection 23 Aug 2021 · 1 repository · arXiv:2108.10360
Tasks archive 2025-07-28
1 task the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Attribute | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections