Activity Prediction
Predict human activities in videos
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
|
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.
ACTIVITY PREDICTION MULTI-TASK LEARNING TRAJECTORY PREDICTION
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
Molecular De Novo Design through Deep Reinforcement Learning
This work introduces a method to tune a sequence-based generative model for molecular de novo design that through augmented episodic likelihood can learn to generate structures with certain specified desirable properties.
SMURFF: a High-Performance Framework for Matrix Factorization
Bayesian Matrix Factorization (BMF) is a powerful technique for recommender systems because it produces good results and is relatively robust against overfitting.
Macau: Scalable Bayesian Multi-relational Factorization with Side Information using MCMC
We propose Macau, a powerful and flexible Bayesian factorization method for heterogeneous data.
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
Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points
CVPR 2018
• fabienbaradel/glimpse_clouds
•
No spatial coherence is forced on the glimpse locations, which gives the module liberty to explore different points at each frame and better optimize the process of scrutinizing visual information.
#5 best model for
Skeleton Based Action Recognition
on N-UCLA
ACTION RECOGNITION IN VIDEOS ACTIVITY PREDICTION HUMAN ACTIVITY RECOGNITION SKELETON BASED ACTION RECOGNITION
Attention-based Multi-Input Deep Learning Architecture for Biological Activity Prediction: An Application in EGFR Inhibitors
These data were trained on a deep learning model which was also integrated with the Attention mechanism to facilitate training and interpreting.
SOTA for Drug Discovery on egfr-inh
Ionospheric activity prediction using convolutional recurrent neural networks
The ionosphere electromagnetic activity is a major factor of the quality of satellite telecommunications, Global Navigation Satellite Systems (GNSS) and other vital space applications.
Can x2vec Save Lives? Integrating Graph and Language Embeddings for Automatic Mental Health Classification
Visualizing graph embeddings annotated with predictions of potentially suicidal individuals shows the integrated model could classify such individuals even if they are positioned far from the support group.
ACTION CLASSIFICATION ACTIVITY PREDICTION DOCUMENT EMBEDDING FEATURE ENGINEERING GRAPH EMBEDDING