Video Prediction
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
|
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.
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.
Deep multi-scale video prediction beyond mean square error
• dyelax/Adversarial_Video_Generation
•
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.
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
• coxlab/prednet
•
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.
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.
SOTA for Semantic Segmentation on CamVid (using extra training data)
Future Frame Prediction for Anomaly Detection -- A New Baseline
• stevenliuwen/ano_pred_cvpr2018
•
To predict a future frame with higher quality for normal events, other than the commonly used appearance (spatial) constraints on intensity and gradient, we also introduce a motion (temporal) constraint in video prediction by enforcing the optical flow between predicted frames and ground truth frames to be consistent, and this is the first work that introduces a temporal constraint into the video prediction task.
Stochastic Adversarial Video Prediction
ICLR 2019
• alexlee-gk/video_prediction
•
Being able to predict what may happen in the future requires an in-depth understanding of the physical and causal rules that govern the world.
Stochastic Adversarial Video Prediction
ICLR 2019
• alexlee-gk/video_prediction
•
However, learning to predict raw future observations, such as frames in a video, is exceedingly challenging -- the ambiguous nature of the problem can cause a naively designed model to average together possible futures into a single, blurry prediction.
Learning to Decompose and Disentangle Representations for Video Prediction
NeurIPS 2018
• jthsieh/DDPAE-video-prediction
•
Our goal is to predict future video frames given a sequence of input frames.