Human action recognition: A taxonomy-based survey, updates, and opportunities

MG Morshed, T Sultana, A Alam, YK Lee - Sensors, 2023 - mdpi.com
Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …

A survey of human action recognition and posture prediction

N Ma, Z Wu, Y Cheung, Y Guo, Y Gao… - Tsinghua Science …, 2022 - ieeexplore.ieee.org
Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …

Skilful nowcasting of extreme precipitation with NowcastNet

Y Zhang, M Long, K Chen, L Xing, R Jin, MI Jordan… - Nature, 2023 - nature.com
Extreme precipitation is a considerable contributor to meteorological disasters and there is a
great need to mitigate its socioeconomic effects through skilful nowcasting that has high …

Simvp: Simpler yet better video prediction

Z Gao, C Tan, L Wu, SZ Li - … of the IEEE/CVF conference on …, 2022 - openaccess.thecvf.com
Abstract From CNN, RNN, to ViT, we have witnessed remarkable advancements in video
prediction, incorporating auxiliary inputs, elaborate neural architectures, and sophisticated …

Earthformer: Exploring space-time transformers for earth system forecasting

Z Gao, X Shi, H Wang, Y Zhu… - Advances in …, 2022 - proceedings.neurips.cc
Conventionally, Earth system (eg, weather and climate) forecasting relies on numerical
simulation with complex physical models and hence is both expensive in computation and …

Temporal attention unit: Towards efficient spatiotemporal predictive learning

C Tan, Z Gao, L Wu, Y Xu, J Xia… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

Openstl: A comprehensive benchmark of spatio-temporal predictive learning

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 …

Extdm: Distribution extrapolation diffusion model for video prediction

Z Zhang, J Hu, W Cheng, D Paudel… - Proceedings of the …, 2024 - openaccess.thecvf.com
Video prediction is a challenging task due to its nature of uncertainty especially for
forecasting a long period. To model the temporal dynamics advanced methods benefit from …

Simvp: Towards simple yet powerful spatiotemporal predictive learning

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 …

Mmvp: Motion-matrix-based video prediction

Y Zhong, L Liang, I Zharkov… - Proceedings of the …, 2023 - openaccess.thecvf.com
A central challenge of video prediction lies where the system has to reason the object's
future motion from image frames while simultaneously maintaining the consistency of its …