Fetching the paper…
Reading the bibliography…
We present a method that learns to integrate temporal information, from a learned dynamics model, with ambiguous visual information, from a learned vision model, in the context of interacting agents.
Tracking and Data Fusion: A Handbook of Algorithms
Yaakov Bar-Shalom, Peter K Willett, and Xin Tian · 2011
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik Kingma and Max Welling · 2014
Earlier work this paper cites.
Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
Earlier work this paper cites.
A recurrent latent variable model for sequential data
Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C Courville, and Yoshua Bengio · 2015
Earlier work this paper cites.
Social LSTM: Human Trajectory Prediction in Crowded Spaces
Alexandre Alahi, Kratarth Goel, Vignesh Ramanathan, Alexandre Robicquet, Li Fei-Fei, and Silvio Savarese · 2016
Earlier work this paper cites.
Interaction networks for learning about objects, relations and physics
Peter W Battaglia, Razvan Pascanu, Matthew Lai, Danilo J Rezende, and Koray Kavukcuoglu · 2016
Earlier work this paper cites.
Generating sentences from a continuous space
Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew M Dai, Rafal Jozefowicz, and Samy Bengio · 2016
Earlier work this paper cites.
Sequential neural models with stochastic layers
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, and Ole Winther · 2016
Earlier work this paper cites.
Learning visual predictive models of physics for playing billiards
Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, and Jitendra Malik · 2016
Earlier work this paper cites.
Backprop KF: Learning discriminative deterministic state estimators
Tuomas Haarnoja, Anurag Ajay, Sergey Levine, and Pieter Abbeel · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Learning physical intuition of block towers by example
Adam Lerer, Sam Gross, and Rob Fergus · 2016
Earlier work this paper cites.
Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun · 2016
Earlier work this paper cites.
Newtonian scene understanding: Unfolding the dynamics of objects in static images
Roozbeh Mottaghi, Hessam Bagherinezhad, Mohammad Rastegari, and Ali Farhadi · 2016
Earlier work this paper cites.
An uncertain future: Forecasting from static images using variational autoencoders
Jacob Walker, Carl Doersch, Abhinav Gupta, and Martial Hebert · 2016
Earlier work this paper cites.
Visual dynamics: Probabilistic future frame synthesis via cross convolutional networks
Tianfan Xue, Jiajun Wu, Katherine Bouman, and Bill Freeman · 2016
Earlier work this paper cites.
A compositional object-based approach to learning physical dynamics
Michael B Chang, Tomer Ullman, Antonio Torralba, and Joshua B Tenenbaum · 2017
Cited alongside, same era.
Taking visual motion prediction to new heightfields
Sebastien Ehrhardt, Aron Monszpart, Niloy Mitra, and Andrea Vedaldi · 2017
Cited alongside, same era.
What will happen next? forecasting player moves in sports videos
Panna Felsen, Pulkit Agrawal, and Jitendra Malik · 2017
Cited alongside, same era.
Z-forcing: Training stochastic recurrent networks
Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, and Yoshua Bengio · 2017
Cited alongside, same era.
VAIN: Attentional multi-agent predictive modeling
Yedid Hoshen · 2017
Cited alongside, same era.
Relational inductive biases, deep learning, and graph networks
Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, and Razvan Pascanu · 2018
Later among the works it cites.
Learning and querying fast generative models for reinforcement learning
Lars Buesing, Theophane Weber, Sebastien Racaniere, S. M. Ali Eslami, Danilo Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, and Daan Wierstra · 2018
Later among the works it cites.
Stochastic video generation with a learned prior
Emily Denton and Rob Fergus · 2018
Later among the works it cites.
Deep tracking in the wild: End-to-end tracking using recurrent neural networks
Julie Dequaire, Peter Ondrúška, Dushyant Rao, Dominic Wang, and Ingmar Posner · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Deep variational bayes filters: Unsupervised learning of state space models from raw data
Maximilian Karl, Maximilian Soelch, Justin Bayer, and Patrick van der Smagt · 2017
Cited alongside, same era.
Activity forecasting
Kris M. Kitani, De-An Huang, and Wei-Chiu Ma · 2017
Cited alongside, same era.
Structured inference networks for nonlinear state space models
Rahul G Krishnan, Uri Shalit, and David Sontag · 2017
Cited alongside, same era.
DESIRE: Distant future prediction in dynamic scenes with interacting agents
Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B Choy, Philip H S Torr, and Manmohan Chandraker · 2017
Cited alongside, same era.
A survey on player tracking in soccer videos
M Manafifard, H Ebadi, and H Abrishami Moghaddam · 2017
Cited alongside, same era.
Identifying basketball plays from sensor data; towards a Low-Cost automatic extraction of advanced statistics
Adria Arbues Sanguesa · 2017
Cited alongside, same era.
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Tim Lillicrap · 2017
Cited alongside, same era.
Social GAN: Socially acceptable trajectories with generative adversarial networks
Agrim Gupta, Justin Johnson, Li Fei-Fei, Silvio Savarese, and Alexandre Alahi · 2018
Later among the works it cites.
Neural relational inference for interacting systems
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, and Richard Zemel · 2018
Later among the works it cites.
Sequential attend, infer, repeat: Generative modelling of moving objects
Adam R Kosiorek, Hyunjik Kim, Ingmar Posner, and Yee Whye Teh · 2018
Later among the works it cites.
Stochastic adversarial video prediction
Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
Later among the works it cites.
Soccer on your tabletop
Konstantinos Rematas, Ira Kemelmacher-Shlizerman, Brian Curless, and Steve Seitz · 2018
Later among the works it cites.
Graph networks as learnable physics engines for inference and control
Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin Riedmiller, Raia Hadsell, and Peter Battaglia · 2018
Later among the works it cites.
MoCoGAN: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
Later among the works it cites.
Relational neural expectation maximization: Unsupervised discovery of objects and their interactions
Sjoerd van Steenkiste, Michael Chang, Klaus Greff, and Jürgen Schmidhuber · 2018
Later among the works it cites.
Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
Later among the works it cites.
Rethinking spatiotemporal feature learning: Speed-accuracy trade-offs in video classification
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2018
Later among the works it cites.
Generative multi-agent behavioral cloning
Eric Zhan, Stephan Zheng, Yisong Yue, Long Sha, and Patrick Lucey · 2018
Later among the works it cites.