Special Section on Image Media Quality
Recent Advances in Video Action Recognition with 3D Convolutions
2021 年 E104.A 巻 6 号 p. 846-856
詳細
2021 年 E104.A 巻 6 号 p. 846-856
The performance of video action recognition has improved significantly in recent decades. Current recognition approaches mainly utilize convolutional neural networks to acquire video feature representations. In addition to the spatial information of video frames, temporal information such as motions and changes is important for recognizing videos. Therefore, the use of convolutions in a spatiotemporal three-dimensional (3D) space for representing spatiotemporal features has garnered significant attention. Herein, we introduce recent advances in 3D convolutions for video action recognition.
