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Accurate spatial-temporal traffic flow forecasting is essential for helping traffic managers take control measures and drivers to choose the optimal travel routes. Recently, graph convolutional ...
Temporal graphs serve as a powerful framework for representing networks whose connections evolve over time. By incorporating time‐stamped interactions, these models capture the dynamic nature of ...
In this paper, we propose a dynamic graph modeling approach to learn spatial-temporal representations for video summarization. Most existing video summarization methods extract image-level features ...
For same-modality stimuli, these results are most closely analogous to temporal or spatial summation, whereby stimuli that are temporally or spatially aligned can activate common perceptual channels.
2025.07.01 🔥 Training codes of I2VGen-XL version have been released. 2025.06.26 🌟 STAR is accepted by ICCV 2025! 2025.01.19 📖 The STAR demo is now available on Google Colab. Feel free to give it a ...