
The Garden of Forking Paths: Towards MultiFuture Trajectory Prediction
This paper studies the problem of predicting the distribution over multi...
read it

VideoBERT: A Joint Model for Video and Language Representation Learning
Selfsupervised learning has become increasingly important to leverage t...
read it

Composing Text and Image for Image Retrieval  An Empirical Odyssey
In this paper, we study the task of image retrieval, where the input que...
read it

Relational Action Forecasting
This paper focuses on multiperson action forecasting in videos. More pr...
read it

Unsupervised Discovery of Parts, Structure, and Dynamics
Humans easily recognize object parts and their hierarchical structure by...
read it

Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Solving complex, temporallyextended tasks is a longstanding problem in...
read it

Stochastic Prediction of MultiAgent Interactions from Partial Observations
We present a method that learns to integrate temporal information, from ...
read it

ActorCentric Relation Network
Current stateoftheart approaches for spatiotemporal action localizat...
read it

Contrastive Bidirectional Transformer for Temporal Representation Learning
This paper aims at learning representations for long sequences of contin...
read it

Floors are Flat: Leveraging Semantics for RealTime Surface Normal Prediction
We propose 4 insights that help to significantly improve the performance...
read it

Unsupervised Learning of Object Structure and Dynamics from Videos
Extracting and predicting object structure and dynamics from videos with...
read it

XGAN: Unsupervised ImagetoImage Translation for ManytoMany Mappings
Style transfer usually refers to the task of applying color and texture ...
read it

An InformationTheoretic Analysis of Deep LatentVariable Models
We present an informationtheoretic framework for understanding tradeof...
read it

Nonlinear functional mapping of the human brain
The field of neuroimaging has truly become data rich, and novel analytic...
read it

Generative Models of Visually Grounded Imagination
It is easy for people to imagine what a man with pink hair looks like, e...
read it

PixColor: Pixel Recursive Colorization
We propose a novel approach to automatically produce multiple colorized ...
read it

Deep Probabilistic Programming
We propose Edward, a Turingcomplete probabilistic programming language....
read it

Progressive Neural Architecture Search
We propose a method for learning CNN structures that is more efficient t...
read it

Contextaware Captions from Contextagnostic Supervision
We introduce an inference technique to produce discriminative contextaw...
read it

Towards Accurate Multiperson Pose Estimation in the Wild
We propose a method for multiperson detection and 2D pose estimation t...
read it

Deep Metric Learning via Facility Location
Learning the representation and the similarity metric in an endtoend f...
read it

Speed/accuracy tradeoffs for modern convolutional object detectors
The goal of this paper is to serve as a guide for selecting a detection ...
read it

Bayesian Dark Knowledge
We consider the problem of Bayesian parameter estimation for deep neural...
read it

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
In this work we address the task of semantic image segmentation with Dee...
read it

A Review of Relational Machine Learning for Knowledge Graphs
Relational machine learning studies methods for the statistical analysis...
read it

Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex s...
read it

Loopy Belief Propagation for Approximate Inference: An Empirical Study
Recently, researchers have demonstrated that loopy belief propagation  ...
read it

Proceedings of the TwentyEighth Conference on Uncertainty in Artificial Intelligence (2012)
This is the Proceedings of the TwentyEighth Conference on Uncertainty i...
read it

RaoBlackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning al...
read it

The Factored Frontier Algorithm for Approximate Inference in DBNs
The Factored Frontier (FF) algorithm is a simple approximate inferenceal...
read it

Semantic Image Segmentation with TaskSpecific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform
Deep convolutional neural networks (CNNs) are the backbone of stateofa...
read it

Detecting events and key actors in multiperson videos
Multiperson event recognition is a challenging task, often with many pe...
read it

A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent Variables
We show how to use a variational approximation to the logistic function ...
read it

Weakly and SemiSupervised Learning of a DCNN for Semantic Image Segmentation
Deep convolutional neural networks (DCNNs) trained on a large number of ...
read it

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Deep Convolutional Neural Networks (DCNNs) have recently shown state of ...
read it

Bayesian structure learning using dynamic programming and MCMC
MCMC methods for sampling from the space of DAGs can mix poorly due to t...
read it

Modeling Discrete Interventional Data using Directed Cyclic Graphical Models
We outline a representation for discrete multivariate distributions in t...
read it

Group Sparse Priors for Covariance Estimation
Recently it has become popular to learn sparse Gaussian graphical models...
read it

Improved Image Captioning via Policy Gradient optimization of SPIDEr
Current image captioning methods are usually trained via (penalized) max...
read it

Generation and Comprehension of Unambiguous Object Descriptions
We propose a method that can generate an unambiguous description (known ...
read it

What's Cookin'? Interpreting Cooking Videos using Text, Speech and Vision
We present a novel method for aligning a sequence of instructions to a v...
read it

Rethinking Spatiotemporal Feature Learning For Video Understanding
In this paper we study 3D convolutional networks for video understanding...
read it

PersonLab: Person Pose Estimation and Instance Segmentation with a BottomUp, PartBased, Geometric Embedding Model
We present a boxfree bottomup approach for the tasks of pose estimatio...
read it

Tracking Emerges by Colorizing Videos
We use large amounts of unlabeled video to learn models for visual track...
read it

Modeling Uncertainty with Hedged Instance Embedding
Instance embeddings are an efficient and versatile image representation ...
read it

NASBench101: Towards Reproducible Neural Architecture Search
Recent advances in neural architecture search (NAS) demand tremendous co...
read it

A view of Estimation of Distribution Algorithms through the lens of ExpectationMaximization
We show that under mild conditions, Estimation of Distribution Algorithm...
read it