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10/20/2022
Rethinking Learning Approaches for Long-Term Action Anticipation
Action anticipation involves predicting future actions having observed t...
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09/01/2022
Continuous-time Particle Filtering for Latent Stochastic Differential Equations
Particle filtering is a standard Monte-Carlo approach for a wide range o...
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05/30/2022
RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
Data imbalance, in which a plurality of the data samples come from a sma...
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05/17/2022
Monotonicity Regularization: Improved Penalties and Novel Applications to Disentangled Representation Learning and Robust Classification
We study settings where gradient penalties are used alongside risk minim...
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02/01/2022
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space
Learning causal relationships in high-dimensional data (images, videos) ...
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10/25/2021
MUSE: Feature Self-Distillation with Mutual Information and Self-Information
We present a novel information-theoretic approach to introduce dependenc...
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08/19/2021
D3D-HOI: Dynamic 3D Human-Object Interactions from Videos
We introduce D3D-HOI: a dataset of monocular videos with ground truth an...
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06/29/2021
Continuous Latent Process Flows
Partial observations of continuous time-series dynamics at arbitrary tim...
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06/20/2021
TD-GEN: Graph Generation With Tree Decomposition
We propose TD-GEN, a graph generation framework based on tree decomposit...
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04/24/2021
Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation
Humans accumulate knowledge in a lifelong fashion. Modern deep neural ne...
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04/24/2021
Adaptive Appearance Rendering
We propose an approach to generate images of people given a desired appe...
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03/17/2021
Learning Discriminative Prototypes with Dynamic Time Warping
Dynamic Time Warping (DTW) is widely used for temporal data processing. ...
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02/25/2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Learning from heterogeneous data poses challenges such as combining data...
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01/21/2021
Activity Graph Transformer for Temporal Action Localization
We introduce Activity Graph Transformer, an end-to-end learnable model f...
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12/08/2020
Neural fidelity warping for efficient robot morphology design
We consider the problem of optimizing a robot morphology to achieve the ...
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07/06/2020
MCMI: Multi-Cycle Image Translation with Mutual Information Constraints
We present a mutual information-based framework for unsupervised image-t...
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03/16/2020
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
This paper proposes a novel graph-constrained generative adversarial net...
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02/24/2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows
Normalizing flows transform a simple base distribution into a complex ta...
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02/24/2020
Variational Hyper RNN for Sequence Modeling
In this work, we propose a novel probabilistic sequence model that excel...
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01/17/2020
Adapting Grad-CAM for Embedding Networks
The gradient-weighted class activation mapping (Grad-CAM) method can fai...
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10/18/2019
Point Process Flows
Event sequences can be modeled by temporal point processes (TPPs) to cap...
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10/02/2019
Graph Generation with Variational Recurrent Neural Network
Generating graph structures is a challenging problem due to the diverse ...
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09/29/2019
Policy Message Passing: A New Algorithm for Probabilistic Graph Inference
A general graph-structured neural network architecture operates on graph...
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09/28/2019
Relational Graph Learning for Crowd Navigation
We present a relational graph learning approach for robotic crowd naviga...
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09/26/2019
COPHY: Counterfactual Learning of Physical Dynamics
Understanding causes and effects in mechanical systems is an essential c...
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08/07/2019
Continuous Graph Flow for Flexible Density Estimation
In this paper, we propose Continuous Graph Flow, a generative continuous...
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07/24/2019
LayoutVAE: Stochastic Scene Layout Generation from a Label Set
Recently there is an increasing interest in scene generation within the ...
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07/23/2019
Lifelong GAN: Continual Learning for Conditional Image Generation
Lifelong learning is challenging for deep neural networks due to their s...
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07/23/2019
Similarity-Preserving Knowledge Distillation
Knowledge distillation is a widely applicable technique for training a s...
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04/05/2019
A Variational Auto-Encoder Model for Stochastic Point Processes
We propose a novel probabilistic generative model for action sequences. ...
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02/26/2019
Learning a Deep ConvNet for Multi-label Classification with Partial Labels
Deep ConvNets have shown great performance for single-label image classi...
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08/13/2018
Time Perception Machine: Temporal Point Processes for the When, Where and What of Activity Prediction
Numerous powerful point process models have been developed to understand...
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08/13/2018
Time Perception Machine: Temporal PointProcesses for the When, Where and What ofActivity Prediction
Numerous powerful point process models have been developed to understand...
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06/16/2018
Object Level Visual Reasoning in Videos
Human activity recognition is typically addressed by training models to ...
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05/23/2018
Distribution Aware Active Learning
Discriminative learning machines often need a large set of labeled sampl...
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03/21/2018
Probabilistic Video Generation using Holistic Attribute Control
Videos express highly structured spatio-temporal patterns of visual data...
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02/18/2018
Structured Label Inference for Visual Understanding
Visual data such as images and videos contain a rich source of structure...
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01/18/2018
Sparsely Connected Convolutional Networks
Residual learning with skip connections permits training ultra-deep neur...
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12/05/2017
Learning to Forecast Videos of Human Activity with Multi-granularity Models and Adaptive Rendering
We propose an approach for forecasting video of complex human activity i...
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07/28/2017
Fine-Pruning: Joint Fine-Tuning and Compression of a Convolutional Network with Bayesian Optimization
When approaching a novel visual recognition problem in a specialized ima...
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06/15/2017
Hierarchical Label Inference for Video Classification
Videos are a rich source of high-dimensional structured data, with a wid...
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06/09/2017
Learning to Learn from Noisy Web Videos
Understanding the simultaneously very diverse and intricately fine-grain...
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06/07/2017
Active Learning for Structured Prediction from Partially Labeled Data
We propose a general purpose active learning algorithm for structured pr...
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06/03/2017
Learning Person Trajectory Representations for Team Activity Analysis
Activity analysis in which multiple people interact across a large space...
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05/30/2017
Generic Tubelet Proposals for Action Localization
We develop a novel framework for action localization in videos. We propo...
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03/29/2017
LabelBank: Revisiting Global Perspectives for Semantic Segmentation
Semantic segmentation requires a detailed labeling of image pixels by ob...
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11/24/2016
Recalling Holistic Information for Semantic Segmentation
Semantic segmentation requires a detailed labeling of image pixels by ob...
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07/09/2016
Hierarchical Deep Temporal Models for Group Activity Recognition
In this paper we present an approach for classifying the activity perfor...
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07/09/2016
Deep Learning of Appearance Models for Online Object Tracking
This paper introduces a novel deep learning based approach for vision ba...
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11/22/2015