Video Prediction
125 papers with code • 13 benchmarks • 17 datasets
Video Prediction is the task of predicting future frames given past video frames.
Source: Photo-Realistic Video Prediction on Natural Videos of Largely Changing Frames
Benchmarks
These leaderboards are used to track progress in Video Prediction
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Libraries
Use these libraries to find Video Prediction models and implementationsDatasets
MNIST
Kinetics
Human3.6M
KTH
Moving MNIST
YouTube-8M
Kinetics-600
Sprites
BAIR Robot Pushing
PHYRE
Most implemented papers
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
coxlab/prednet
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Here, we explore prediction of future frames in a video sequence as an unsupervised learning rule for learning about the structure of the visual world.
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
ndrplz/ConvLSTM_pytorch
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NeurIPS 2015
The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time.
Video-to-Video Synthesis
NVIDIA/vid2vid
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NeurIPS 2018
We study the problem of video-to-video synthesis, whose goal is to learn a mapping function from an input source video (e. g., a sequence of semantic segmentation masks) to an output photorealistic video that precisely depicts the content of the source video.
Deep multi-scale video prediction beyond mean square error
dyelax/Adversarial_Video_Generation
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Learning to predict future images from a video sequence involves the construction of an internal representation that models the image evolution accurately, and therefore, to some degree, its content and dynamics.
The "something something" video database for learning and evaluating visual common sense
jayleicn/singularity
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ICCV 2017
Neural networks trained on datasets such as ImageNet have led to major advances in visual object classification.
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning
Yunbo426/predrnn-pp
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ICML 2018
We present PredRNN++, an improved recurrent network for video predictive learning.
Learning a Driving Simulator
commaai/research
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Comma. ai's approach to Artificial Intelligence for self-driving cars is based on an agent that learns to clone driver behaviors and plans maneuvers by simulating future events in the road.
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Hzzone/Precipitation-Nowcasting
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NeurIPS 2017
To address these problems, we propose both a new model and a benchmark for precipitation nowcasting.
Prediction Under Uncertainty with Error-Encoding Networks
mbhenaff/EEN
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In this work we introduce a new framework for performing temporal predictions in the presence of uncertainty.
Stochastic Video Generation with a Learned Prior
edenton/svg
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ICML 2018
Sample generations are both varied and sharp, even many frames into the future, and compare favorably to those from existing approaches.
