b'Greg Mori'

research

∙ 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...

Yu Gong, et al. ∙

research

∙ 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...

João Monteiro, et al. ∙

research

∙ 02/01/2022

Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space

Learning causal relationships in high-dimensional data (images, videos) ...

Steeven Janny, et al. ∙

research

∙ 10/25/2021

MUSE: Feature Self-Distillation with Mutual Information and Self-Information

We present a novel information-theoretic approach to introduce dependenc...

Yu Gong, et al. ∙

research

∙ 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...

Xiang Xu, et al. ∙

research

∙ 06/29/2021

Continuous Latent Process Flows

Partial observations of continuous time-series dynamics at arbitrary tim...

Ruizhi Deng, et al. ∙

research

∙ 06/20/2021

TD-GEN: Graph Generation With Tree Decomposition

We propose TD-GEN, a graph generation framework based on tree decomposit...

Hamed Shirzad, et al. ∙

research

∙ 04/24/2021

Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation

Humans accumulate knowledge in a lifelong fashion. Modern deep neural ne...

Mengyao Zhai, et al. ∙

research

∙ 04/24/2021

Adaptive Appearance Rendering

We propose an approach to generate images of people given a desired appe...

Mengyao Zhai, et al. ∙

research

∙ 03/17/2021

Learning Discriminative Prototypes with Dynamic Time Warping

Dynamic Time Warping (DTW) is widely used for temporal data processing. ...

Xiaobin Chang, et al. ∙

research

∙ 02/25/2021

Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data

Learning from heterogeneous data poses challenges such as combining data...

Yu Gong, et al. ∙

research

∙ 01/21/2021

Activity Graph Transformer for Temporal Action Localization

We introduce Activity Graph Transformer, an end-to-end learnable model f...

Megha Nawhal, et al. ∙

research

∙ 12/08/2020

Neural fidelity warping for efficient robot morphology design

We consider the problem of optimizing a robot morphology to achieve the ...

Sha Hu, et al. ∙

research

∙ 07/06/2020

MCMI: Multi-Cycle Image Translation with Mutual Information Constraints

We present a mutual information-based framework for unsupervised image-t...

Xiang Xu, et al. ∙

research

∙ 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...

Nelson Nauata, et al. ∙

research

∙ 02/24/2020

Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows

Normalizing flows transform a simple base distribution into a complex ta...

Ruizhi Deng, et al. ∙

research

∙ 02/24/2020

Variational Hyper RNN for Sequence Modeling

In this work, we propose a novel probabilistic sequence model that excel...

Ruizhi Deng, et al. ∙

research

∙ 01/17/2020

Adapting Grad-CAM for Embedding Networks

The gradient-weighted class activation mapping (Grad-CAM) method can fai...

Lei Chen, et al. ∙

research

∙ 10/18/2019

Point Process Flows

Event sequences can be modeled by temporal point processes (TPPs) to cap...

Nazanin Mehrasa, et al. ∙

research

∙ 10/02/2019

Graph Generation with Variational Recurrent Neural Network

Generating graph structures is a challenging problem due to the diverse ...

Shih-Yang Su, et al. ∙

research

∙ 09/29/2019

Policy Message Passing: A New Algorithm for Probabilistic Graph Inference

A general graph-structured neural network architecture operates on graph...

Zhiwei Deng, et al. ∙

research

∙ 09/28/2019

Relational Graph Learning for Crowd Navigation

We present a relational graph learning approach for robotic crowd naviga...

Changan Chen, et al. ∙

research

∙ 09/26/2019

COPHY: Counterfactual Learning of Physical Dynamics

Understanding causes and effects in mechanical systems is an essential c...

Fabien Baradel, et al. ∙

research

∙ 08/07/2019

Continuous Graph Flow for Flexible Density Estimation

In this paper, we propose Continuous Graph Flow, a generative continuous...

Zhiwei Deng, et al. ∙

research

∙ 07/24/2019

LayoutVAE: Stochastic Scene Layout Generation from a Label Set

Recently there is an increasing interest in scene generation within the ...

Akash Abdu Jyothi, et al. ∙

research

∙ 07/23/2019

Lifelong GAN: Continual Learning for Conditional Image Generation

Lifelong learning is challenging for deep neural networks due to their s...

Mengyao Zhai, et al. ∙

research

∙ 07/23/2019

Similarity-Preserving Knowledge Distillation

Knowledge distillation is a widely applicable technique for training a s...

Frederick Tung, et al. ∙

research

∙ 04/05/2019

A Variational Auto-Encoder Model for Stochastic Point Processes

We propose a novel probabilistic generative model for action sequences. ...

Nazanin Mehrasa, et al. ∙

research

∙ 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...

Thibaut Durand, et al. ∙

research

∙ 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...

Yatao Zhong, et al. ∙

research

∙ 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...

Yatao Zhong, et al. ∙

research

∙ 06/16/2018

Object Level Visual Reasoning in Videos

Human activity recognition is typically addressed by training models to ...

Fabien Baradel, et al. ∙

research

∙ 05/23/2018

Distribution Aware Active Learning

Discriminative learning machines often need a large set of labeled sampl...

Arash Mehrjou, et al. ∙

research

∙ 03/21/2018

Probabilistic Video Generation using Holistic Attribute Control

Videos express highly structured spatio-temporal patterns of visual data...

Jiawei He, et al. ∙

research

∙ 02/18/2018

Structured Label Inference for Visual Understanding

Visual data such as images and videos contain a rich source of structure...

Nelson Nauata, et al. ∙

research

∙ 01/18/2018

Sparsely Connected Convolutional Networks

Residual learning with skip connections permits training ultra-deep neur...

Ligeng Zhu, et al. ∙

research

∙ 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...

Mengyao Zhai, et al. ∙

research

∙ 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...

Frederick Tung, et al. ∙

research

∙ 06/15/2017

Hierarchical Label Inference for Video Classification

Videos are a rich source of high-dimensional structured data, with a wid...

Nelson Nauata, et al. ∙

research

∙ 06/09/2017

Learning to Learn from Noisy Web Videos

Understanding the simultaneously very diverse and intricately fine-grain...

Serena Yeung, et al. ∙

research

∙ 06/07/2017

Active Learning for Structured Prediction from Partially Labeled Data

We propose a general purpose active learning algorithm for structured pr...

Mehran Khodabandeh, et al. ∙

research

∙ 06/03/2017

Learning Person Trajectory Representations for Team Activity Analysis

Activity analysis in which multiple people interact across a large space...

Nazanin Mehrasa, et al. ∙

research

∙ 05/30/2017

Generic Tubelet Proposals for Action Localization

We develop a novel framework for action localization in videos. We propo...

Jiawei He, et al. ∙

research

∙ 03/29/2017

LabelBank: Revisiting Global Perspectives for Semantic Segmentation

Semantic segmentation requires a detailed labeling of image pixels by ob...

Hexiang Hu, et al. ∙

research

∙ 11/24/2016

Recalling Holistic Information for Semantic Segmentation

Semantic segmentation requires a detailed labeling of image pixels by ob...

Hexiang Hu, et al. ∙

research

∙ 07/09/2016

Hierarchical Deep Temporal Models for Group Activity Recognition

In this paper we present an approach for classifying the activity perfor...

Mostafa S. Ibrahim, et al. ∙

research

∙ 07/09/2016

Deep Learning of Appearance Models for Online Object Tracking

This paper introduces a novel deep learning based approach for vision ba...

Mengyao Zhai, et al. ∙

research

∙ 11/22/2015

End-to-end Learning of Action Detection from Frame Glimpses in Videos

In this work we introduce a fully end-to-end approach for action detecti...

Serena Yeung, et al. ∙

research

∙ 11/13/2015

Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition

Rich semantic relations are important in a variety of visual recognition...

Zhiwei Deng, et al. ∙

research

∙ 07/21/2015

Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos

Every moment counts in action recognition. A comprehensive understanding...

Serena Yeung, et al. ∙

Greg Mori

Featured Co-authors