Apr 4, 2023 · The purpose of this operation is to obtain more fine-grained segment features by extracting memory representation from shorter sequences. Then ...
To implement it, our model elaborates a novel pretext task of identifying latent sequences and normal frames by training self-supervised generative adversarial ...
Video summarisation can relieve the pressure on video storage, transmission, archiving, and retrieval caused by the explosive growth of online videos in ...
Therefore, a recurrent unit augmented memory network (RUAMN) for video summarisation is proposed, which effectively utilises the long-term memory extraction ...
Abstract. In recent years, supervised video summarization has achieved promising progress with various recurrent neural networks (RNNs) based methods, which ...
Missing: summarisation. | Show results with:summarisation.
Dec 13, 2023 · This paper explores Memory-Augmented Neural Networks (MANNs), delving into how they blend human-like memory processes into AI.
Abstract. We propose a novel supervised learning technique for sum- marizing videos by automatically selecting keyframes or key subshots.
We integrate the self-attention mechanism and a fully convolutional sequence network to capture the global and local temporal dependencies of video frames.
Jun 24, 2024 · The magic behind these feats of artificial intelligence often involves a powerful neural network known as a Gated Recurrent Unit, or GRU.
Oct 25, 2019 · ABSTRACT. In recent years, supervised video summarization has achieved promising progress with various recurrent neural networks.
Missing: summarisation. | Show results with:summarisation.