About
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
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Subtasks
Datasets
Greatest papers with code
Unsupervised Learning for Physical Interaction through Video Prediction
NeurIPS 2016
• tensorflow/models
• 
A core challenge for an agent learning to interact with the world is to predict how its actions affect objects in its environment.
Unsupervised Learning of Object Structure and Dynamics from Videos
NeurIPS 2019
• google-research/google-research
•
Extracting and predicting object structure and dynamics from videos without supervision is a major challenge in machine learning.
ACTION RECOGNITION CONTINUOUS CONTROL OBJECT TRACKING VIDEO PREDICTION
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation
ICLR 2020
• tensorflow/tensor2tensor
•
Generative models that can model and predict sequences of future events can, in principle, learn to capture complex real-world phenomena, such as physical interactions.
Model-Based Reinforcement Learning for Atari
We describe Simulated Policy Learning (SimPLe), a complete model-based deep RL algorithm based on video prediction models and present a comparison of several model architectures, including a novel architecture that yields the best results in our setting.
ATARI GAMES MODEL-BASED REINFORCEMENT LEARNING VIDEO PREDICTION
Video-to-Video Synthesis
NeurIPS 2018
• NVIDIA/vid2vid
• 
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.
SEMANTIC SEGMENTATION VIDEO PREDICTION VIDEO-TO-VIDEO SYNTHESIS
Learning a Driving Simulator
• commaai/research
•
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.
Improving Semantic Segmentation via Video Propagation and Label Relaxation
CVPR 2019
• NVIDIA/semantic-segmentation
•
In this paper, we present a video prediction-based methodology to scale up training sets by synthesizing new training samples in order to improve the accuracy of semantic segmentation networks.
Ranked #1 on
Semantic Segmentation
on KITTI Semantic Segmentation
(using extra training data)
SDCNet: Video Prediction Using Spatially-Displaced Convolution
• NVIDIA/semantic-segmentation
•
We present an approach for high-resolution video frame prediction by conditioning on both past frames and past optical flows.
SDC-Net: Video prediction using spatially-displaced convolution
ECCV 2018
• NVIDIA/semantic-segmentation
•
We present an approach for high-resolution video frame prediction by conditioning on both past frames and past optical flows.
Ranked #1 on
Video Prediction
on YouTube-8M
Scalable Gradients for Stochastic Differential Equations
The adjoint sensitivity method scalably computes gradients of solutions to ordinary differential equations.
Ranked #1 on
Video Prediction
on CMU Mocap-2