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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.
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.