MotionRNN: A flexible model for video prediction with spacetime-varying motions
This paper tackles video prediction from a new dimension of predicting spacetime-varying
motions that are incessantly changing across both space and time. Prior methods mainly …
motions that are incessantly changing across both space and time. Prior methods mainly …
Infinitenature-zero: Learning perpetual view generation of natural scenes from single images
We present a method for learning to generate unbounded flythrough videos of natural
scenes starting from a single view. This capability is learned from a collection of single …
scenes starting from a single view. This capability is learned from a collection of single …
Mau: A motion-aware unit for video prediction and beyond
Accurately predicting inter-frame motion information plays a key role in video prediction
tasks. In this paper, we propose a Motion-Aware Unit (MAU) to capture reliable inter-frame …
tasks. In this paper, we propose a Motion-Aware Unit (MAU) to capture reliable inter-frame …
Learning to decompose and disentangle representations for video prediction
Our goal is to predict future video frames given a sequence of input frames. Despite large
amounts of video data, this remains a challenging task because of the high-dimensionality of …
amounts of video data, this remains a challenging task because of the high-dimensionality of …
Video coding for machines: A paradigm of collaborative compression and intelligent analytics
Video coding, which targets to compress and reconstruct the whole frame, and feature
compression, which only preserves and transmits the most critical information, stand at two …
compression, which only preserves and transmits the most critical information, stand at two …
Learning to generate long-term future via hierarchical prediction
We propose a hierarchical approach for making long-term predictions of future frames. To
avoid inherent compounding errors in recursive pixel-level prediction, we propose to first …
avoid inherent compounding errors in recursive pixel-level prediction, we propose to first …
Video prediction recalling long-term motion context via memory alignment learning
Our work addresses long-term motion context issues for predicting future frames. To predict
the future precisely, it is required to capture which long-term motion context (eg, walking or …
the future precisely, it is required to capture which long-term motion context (eg, walking or …
Adversarial video generation on complex datasets
Generative models of natural images have progressed towards high fidelity samples by the
strong leveraging of scale. We attempt to carry this success to the field of video modeling by …
strong leveraging of scale. We attempt to carry this success to the field of video modeling by …
基于计算机视觉的Transformer 研究进展.
刘文婷， 卢新明 - Journal of Computer Engineering & …, 2022 - search.ebscohost.com
Transformer 是一种基于自注意力机制, 并行化处理数据的深度神经网络. 近几年基于
Transformer 的模型成为计算机视觉任务的重要研究方向. 针对目前国内基于Transformer …
Transformer 的模型成为计算机视觉任务的重要研究方向. 针对目前国内基于Transformer …
Video anomaly detection with sparse coding inspired deep neural networks
This paper presents an anomaly detection method that is based on a sparse coding inspired
Deep Neural Networks (DNN). Specifically, in light of the success of sparse coding based …
Deep Neural Networks (DNN). Specifically, in light of the success of sparse coding based …