Feb 15, 2017 · In this work, we represent the hierarchical structure of video with multiple granularities including, from short to long, single frame, consecutive frames ( ...
To interpret deep neural networks, one main approach is to dissect the visual input and find the prototypical parts responsible for the classification.
Jul 20, 2020 · In this paper, we present hierarchical contrastive motion learning, a new self-supervised learning framework to extract effective motion representations from ...
Therefore, in this work, we represent the hierarchical structure of video with multiple granularities including, from short to long, single frame, consecutive ...
Therefore, in this work, we represent the hierarchical structure of video with multiple granularities including, from short to long, single frame, consecutive ...
It is not surprising that the motion features at higher lev- els achieve higher accuracy than the ones at lower levels as the former possess more useful.
Jan 5, 2023 · We propose HierVL, a novel hierarchical video-language embedding that simultaneously accounts for both long-term and short-term associations.
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Jan 27, 2022 · Hierarchical clustering multi-task learning for joint human action grouping and recognition. IEEE Transactions on Pattern Analysis and ...
This thesis proposes several formulations and extensions of deep learning methods which learn hierarchical representations for three challenging video ...
Consequently, the whole framework utilizes multi-stream CNNs to learn a hierarchical representation that captures spatial and temporal information of video. To ...