A note on detection of sports action based on temporal cycle consistency learning
Tsuyoshi Masuda, Ren Togo, Takahiro Ogawa, Miki Haseyama · 2021
This paper presents a method for action detection based on Temporal Cycle Consistency(TCC) Learning. The proposed method realizes the action detection of flexible length segments based on a frame-level action prediction technique. We enable calculation of similarities for spatio-temporal features based on TCC to detect target actions from input videos. Finally, our method determines temporal segments by smoothing the frame-level action detection result. Experimental results show the validity of the proposed method.