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Hypergraph Transformer for Skeleton-based Action Recognition
This is the official implementation of our paper "Hypergraph Transformer for Skeleton-based Action Recognition." Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections. By defining a graph with joints as vertices and their natural connections as edges, previous works successfully adopted Graph Convolutional networks (GCNs) to model joint co-occurrences and achieved superior performance.
An implementation of the Joint Generation Algorithm of Fredman and Khachiyan for the computation of a dual pair of monotone boolean formulas in DNF (hypergraph transversals, extreme rays of polyhedral cones...). User-replaceable oracle.
A mediawiki extension supplying a set of parser functions to generate and display graphviz, freemind and hypergraph graphs from the content of a semantic mediawiki, and parsing an uploaded freemind file.
Graph visualization using hyperbolic geometry (hyperbolic trees, but also general graphs).
Applications cover web site structures, topic maps, organisational charts and wikis.
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hgboost is a header-only library which contains a generic hypergraph implementation and provides vertex/node contraction and vertex/edge filtering. It contains algorithms to compute cohesive subgroups, minimum cuts and maximum flows.