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In recent years, Internet of Things (IoT) has made rapid development, and IoT devices are developing toward intelligence. IoT terminal devices represented by surveillance cameras play an irreplaceable role in modern society, most of them are integrated with video action recognition and other intelligent functions. However, their performance is somewhat affected by the limitation of computing resources of IoT terminal devices and the lack of long-range nonlinear temporal relation modeling and reverse motion information modeling. To address this urgent problem, we introduce a startling temporal transformer network with self-supervision (TTSN). Our high-performance TTSN mainly consists of a temporal transformer module and a temporal sequence self-supervision (TSS) module. Concisely speaking, we utilize the efficient temporal transformer module to model the nonlinear temporal dependencies among …