Future prediction
29 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Future prediction
CCD
Most implemented papers
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.
Peeking into the Future: Predicting Future Person Activities and Locations in Videos
google/next-prediction
•
•
CVPR 2019
To facilitate the training, the network is learned with an auxiliary task of predicting future location in which the activity will happen.
Compositional Video Prediction
JudyYe/CVP
•
•
ICCV 2019
We present an approach for pixel-level future prediction given an input image of a scene.
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
The derived uncertainty-based ranking loss is found to significantly boost model performance by improving the quality of relational features.
Interpreting Tree Ensembles with inTrees
Tree ensembles such as random forests and boosted trees are accurate but difficult to understand, debug and deploy.
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.
Improving Video Generation for Multi-functional Applications
bernhard2202/improved-video-gan
•
•
In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications.
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.
Probabilistic Video Generation using Holistic Attribute Control
charlescheng0117/pytorch-VideoVAE
•
•
ECCV 2018
Videos express highly structured spatio-temporal patterns of visual data.
Deep RNN Framework for Visual Sequential Applications
BoPang1996/Deep-RNN-Framework
•
•
CVPR 2019
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.
