Y Wang, M Long, J Wang, Z Gao… - Advances in neural …, 2017 - proceedings.neurips.cc
The predictive learning of spatiotemporal sequences aims to generate future images by learning from the historical frames, where spatial appearances and temporal variations are …
C Tan, Z Gao, S Li, SZ Li - arXiv preprint arXiv:2211.12509, 2022 - arxiv.org
Recent years have witnessed remarkable advances in spatiotemporal predictive learning, incorporating auxiliary inputs, elaborate neural architectures, and sophisticated training …
C Tan, S Li, Z Gao, W Guan, Z Wang… - Advances in …, 2023 - proceedings.neurips.cc
Spatio-temporal predictive learning is a learning paradigm that enables models to learn spatial and temporal patterns by predicting future frames from given past frames in an …
Y Wang, Z Gao, M Long, J Wang… - … on machine learning, 2018 - proceedings.mlr.press
We present PredRNN++, a recurrent network for spatiotemporal predictive learning. In pursuit of a great modeling capability for short-term video dynamics, we make our network …
Spatiotemporal predictive learning aims to generate future frames by learning from historical frames. In this paper, we investigate existing methods and present a general framework of …
Y Wang, J Zhang, H Zhu, M Long… - Proceedings of the …, 2019 - openaccess.thecvf.com
Natural spatiotemporal processes can be highly non-stationary in many ways, eg the low- level non-stationarity such as spatial correlations or temporal dependencies of local pixel …
Learning from spatio-temporal data has numerous applications such as human-behavior analysis, object tracking, video compression, and physics simulation. However, existing …
X Zha, W Zhu, L Xun, S Yang… - Advances in Neural …, 2021 - proceedings.neurips.cc
Spatio-temporal representational learning has been widely adopted in various fields such as action recognition, video object segmentation, and action anticipation. Previous spatio …