NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 42; no. 10; pp. 2684 - 2701
• Main Authors: Liu, Jun, Shahroudy, Amir, Perez, Mauricio, Wang, Gang, Duan, Ling-Yu, Kot, Alex C.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D action recognition; Activity understanding; Benchmark testing; Benchmarks; Cameras; Datasets; Deep learning; Human activity recognition; Human motion; large-scale benchmark; Lighting; Machine learning; Performance evaluation; RGB plus D vision; RGB+D vision; Semantics; Skeleton; Three-dimensional displays; video analysis

Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-based and RGB+D-based action recognition benchmarks have a number of limitations, including the lack of large-scale trai...