Future prediction
Leaderboards
Greatest papers with code
Peeking into the Future: Predicting Future Person Activities and Locations in Videos
CVPR 2019
• google/next-prediction
• 
To facilitate the training, the network is learned with an auxiliary task of predicting future location in which the activity will happen.
SOTA for Activity Prediction on ActEV
ACTIVITY PREDICTION FUTURE PREDICTION MOTION FORECASTING MULTI-TASK LEARNING TRAJECTORY PREDICTION
Decomposing Motion and Content for Natural Video Sequence Prediction
• rubenvillegas/iclr2017mcnet
•
To the best of our knowledge, this is the first end-to-end trainable network architecture with motion and content separation to model the spatiotemporal dynamics for pixel-level future prediction in natural videos.
Interpreting Tree Ensembles with inTrees
Tree ensembles such as random forests and boosted trees are accurate but difficult to understand, debug and deploy.
INFER: INtermediate representations for FuturE pRediction
• talsperre/INFER
• 
Uncharacteristic of state-of-the-art approaches, our representations and models generalize to completely different datasets, collected across several cities, and also across countries where people drive on opposite sides of the road (left-handed vs right-handed driving).
ACTIVITY PREDICTION FUTURE PREDICTION MULTI-OBJECT TRACKING TRAJECTORY PREDICTION
Deep RNN Framework for Visual Sequential Applications
CVPR 2019
• BoPang1996/Deep-RNN-Framework
•
There are mainly two novel designs in our deep RNN framework: one is a new RNN module called Context Bridge Module (CBM) which splits the information flowing along the sequence (temporal direction) and along depth (spatial representation direction), making it easier to train when building deep by balancing these two directions; the other is the Overlap Coherence Training Scheme that reduces the training complexity for long visual sequential tasks on account of the limitation of computing resources.
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
DESIRE effectively predicts future locations of objects in multiple scenes by 1) accounting for the multi-modal nature of the future prediction (i. e., given the same context, future may vary), 2) foreseeing the potential future outcomes and make a strategic prediction based on that, and 3) reasoning not only from the past motion history, but also from the scene context as well as the interactions among the agents.
Learning Representations for Predicting Future Activities
Foreseeing the future is one of the key factors of intelligence.
Probabilistic Video Generation using Holistic Attribute Control
ECCV 2018
• charlescheng0117/pytorch-VideoVAE
•
Videos express highly structured spatio-temporal patterns of visual data.
Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression
• yuriautsumi/PersonalizedGP
•
In this paper, we introduce the use of a personalized Gaussian Process model (pGP) to predict the key metrics of Alzheimer's Disease progression (MMSE, ADAS-Cog13, CDRSB and CS) based on each patient's previous visits.
Improving Video Generation for Multi-functional Applications
In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications.
COLORIZATION FUTURE PREDICTION VIDEO GENERATION VIDEO INPAINTING