Aug 10, 2022 · This work attempts to model the long-term spatio-temporal information of the video based on a variant of RNN, ie, higher-order RNN.

Dec 31, 2021 · Therefore, this work attempts to model the long-term spatio-temporal information of the video based on a variant of RNN, i.e., higher-order RNN.

Although recurrent neural networks (RNNs) are widely leveraged to process temporal or sequential data, they have attracted too little attention in current ...

LSN: Long-Term Spatio-Temporal Network for Video Recognition. https://doi.org/10.1007/978-981-19-5194-7_24. Journal: Communications in Computer and ...

Moreover, we propose a novel long-term spatio-temporal network (LSN) for solving this video task, the core of which integrates the newly constructed high-order ...

LSN: Long-Term Spatio-Temporal Network for Video Recognition. Chapter © 2022. PSRUNet: a recurrent neural network for spatiotemporal sequence forecasting ...

Most existing video summarization methods mainly employ recurrent neural networks to capture long-term dependencies in videos, yielding remarkable results.

Nov 3, 2022 · In Ref. [9], a long-term recurrent convolutional network is proposed and verified to be helpful for action classification. Ng et al. [ ...

This paper presents a general ConvNet architecture for video action recognition based on multiplicative interac- tions of spacetime features.

Apr 19, 2021 · It is through this mechanism that LSTMs are able to capture both short and long-term temporal patterns in the data. Convolutional LSTMs ...