Georgia Institute of Technology

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The Georgia Institute of Technology, commonly referred to as Georgia Tech, is a public research university and institute of technology in Atlanta, Georgia.

REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild

In recent years, significant attention has been devoted towards integrat...
01/29/2020 ∙ by Rahul Duggal, et al. ∙ 116 ∙ share

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Predicting A Creator's Preferences In, and From, Interactive Generative Art

As a lay user creates an art piece using an interactive generative art t...
03/03/2020 ∙ by Devi Parikh, et al. ∙ 92 ∙ share

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Deep Reinforcement Learning with Smooth Policy

Deep neural networks have been widely adopted in modern reinforcement le...
03/21/2020 ∙ by Qianli Shen, et al. ∙ 54 ∙ share

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Audio-Visual Scene-Aware Dialog

We introduce the task of scene-aware dialog. Given a follow-up question ...
01/25/2019 ∙ by Huda Alamri, et al. ∙ 48 ∙ share

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nocaps: novel object captioning at scale

Image captioning models have achieved impressive results on datasets con...
12/20/2018 ∙ by Harsh Agrawal, et al. ∙ 46 ∙ share

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Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation

Generative Adversarial Networks (GANs) have achieved great success in un...
02/10/2020 ∙ by Minshuo Chen, et al. ∙ 45 ∙ share

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SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions

Existing VQA datasets contain questions with varying levels of complexit...
01/20/2020 ∙ by Ramprasaath R. Selvaraju, et al. ∙ 44 ∙ share

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The role of visual saliency in the automation of seismic interpretation

In this paper, we propose a workflow based on SalSi for the detection an...
12/31/2018 ∙ by Muhammad Amir Shafiq, et al. ∙ 40 ∙ share

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Continuous Online Learning and New Insights to Online Imitation Learning

Online learning is a powerful tool for analyzing iterative algorithms. H...
12/03/2019 ∙ by Jonathan Lee, et al. ∙ 33 ∙ share

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Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning

Deep neural networks (DNNs) are increasingly powering high-stakes applic...
01/21/2020 ∙ by Nilaksh Das, et al. ∙ 33 ∙ share

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CNN 101: Interactive Visual Learning for Convolutional Neural Networks

The success of deep learning solving previously-thought hard problems ha...
01/07/2020 ∙ by Zijie J. Wang, et al. ∙ 27 ∙ share

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Learning to Walk in the Real World with Minimal Human Effort

Reliable and stable locomotion has been one of the most fundamental chal...
02/20/2020 ∙ by Sehoon Ha, et al. ∙ 27 ∙ share

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Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded

Many vision and language models suffer from poor visual grounding - ofte...
02/11/2019 ∙ by Ramprasaath R. Selvaraju, et al. ∙ 26 ∙ share

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Perceptual Attention-based Predictive Control

In this paper, we present a novel information processing architecture fo...
04/26/2019 ∙ by Keuntaek Lee, et al. ∙ 26 ∙ share

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Automatically Neutralizing Subjective Bias in Text

Texts like news, encyclopedias, and some social media strive for objecti...
11/21/2019 ∙ by Reid Pryzant, et al. ∙ 26 ∙ share

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EvalAI: Towards Better Evaluation Systems for AI Agents

We introduce EvalAI, an open source platform for evaluating and comparin...
02/10/2019 ∙ by Deshraj Yadav, et al. ∙ 24 ∙ share

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GOGGLES: Automatic Training Data Generation with Affinity Coding

Generating large labeled training data is becoming the biggest bottlenec...
03/11/2019 ∙ by Nilaksh Das, et al. ∙ 24 ∙ share

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Probabilistic Kernel Support Vector Machines

We propose a probabilistic enhancement of standard kernel Support Vecto...
04/14/2019 ∙ by Yongxin Chen, et al. ∙ 24 ∙ share

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Good Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency

Analysis of state-of-the-art VO/VSLAM system exposes a gap in balancing ...
01/03/2020 ∙ by Yipu Zhao, et al. ∙ 24 ∙ share

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Trick or TReAT: Thematic Reinforcement for Artistic Typography

An approach to make text visually appealing and memorable is semantic re...
03/19/2019 ∙ by Purva Tendulkar, et al. ∙ 23 ∙ share

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TarMAC: Targeted Multi-Agent Communication

We explore a collaborative multi-agent reinforcement learning setting wh...
10/26/2018 ∙ by Abhishek Das, et al. ∙ 22 ∙ share

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Synthesizing New Retinal Symptom Images by Multiple Generative Models

Age-Related Macular Degeneration (AMD) is an asymptomatic retinal diseas...
02/11/2019 ∙ by Yi-Chieh Liu, et al. ∙ 22 ∙ share

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Meta Learning with Relational Information for Short Sequences

This paper proposes a new meta-learning method -- named HARMLESS (HAwkes...
09/04/2019 ∙ by Yujia Xie, et al. ∙ 22 ∙ share

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Learning Robust Representations with Graph Denoising Policy Network

Graph representation learning, aiming to learn low-dimensional represent...
10/04/2019 ∙ by Lu Wang, et al. ∙ 21 ∙ share

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Pose estimation and bin picking for deformable products

Robotic systems in manufacturing applications commonly assume known obje...
11/12/2019 ∙ by Benjamin Joffe, et al. ∙ 21 ∙ share

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Lemotif: Abstract Visual Depictions of your Emotional States in Life

We present Lemotif. Lemotif generates a motif for your emotional life. Y...
03/18/2019 ∙ by Devi Parikh, et al. ∙ 20 ∙ share

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Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data

Deep neural networks have attained remarkable performance when applied t...
02/26/2020 ∙ by Yen-Chang Hsu, et al. ∙ 20 ∙ share

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Evolving Neural Networks through a Reverse Encoding Tree

NeuroEvolution is one of the most competitive evolutionary learning fram...
02/03/2020 ∙ by Haoling Zhang, et al. ∙ 19 ∙ share

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CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog

Visual Dialog is a multimodal task of answering a sequence of questions ...
03/07/2019 ∙ by Satwik Kottur, et al. ∙ 18 ∙ share

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Unsupervised Discovery of Decision States for Transfer in Reinforcement Learning

We present a hierarchical reinforcement learning (HRL) or options framew...
07/24/2019 ∙ by Nirbhay Modhe, et al. ∙ 17 ∙ share

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Detecting Robotic Affordances on Novel Objects with Regional Attention and Attributes

This paper presents a framework for predicting affordances of object par...
09/12/2019 ∙ by Fu-Jen Chu, et al. ∙ 17 ∙ share

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Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance

Individual neurons in convolutional neural networks supervised for image...
08/08/2018 ∙ by Ramprasaath R. Selvaraju, et al. ∙ 16 ∙ share

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Fast 3D Pose Refinement with RGB Images

Pose estimation is a vital step in many robotics and perception tasks su...
11/17/2019 ∙ by Abhinav Jain, et al. ∙ 16 ∙ share

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Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline

Prior work in visual dialog has focused on training deep neural models o...
12/05/2019 ∙ by Vishvak Murahari, et al. ∙ 16 ∙ share

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Learning Structured Communication for Multi-agent Reinforcement Learning

This work explores the large-scale multi-agent communication mechanism u...
02/11/2020 ∙ by Junjie Sheng, et al. ∙ 16 ∙ share

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Cycle-Consistency for Robust Visual Question Answering

Despite significant progress in Visual Question Answering over the years...
02/15/2019 ∙ by Meet Shah, et al. ∙ 14 ∙ share

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Traffic Sign Detection under Challenging Conditions: A Deeper Look Into Performance Variations and Spectral Characteristics

Traffic signs are critical for maintaining the safety and efficiency of ...
08/29/2019 ∙ by Dogancan Temel, et al. ∙ 14 ∙ share

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Do Explanations make VQA Models more Predictable to a Human?

A rich line of research attempts to make deep neural networks more trans...
10/29/2018 ∙ by Arjun Chandrasekaran, et al. ∙ 13 ∙ share

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Response to "Visual Dialogue without Vision or Dialogue" (Massiceti et al., 2018)

In a recent workshop paper, Massiceti et al. presented a baseline model ...
01/16/2019 ∙ by Abhishek Das, et al. ∙ 12 ∙ share

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Let's Transfer Transformations of Shared Semantic Representations

With a good image understanding capability, can we manipulate the images...
03/02/2019 ∙ by Nam Vo, et al. ∙ 12 ∙ share

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Embodied Question Answering in Photorealistic Environments with Point Cloud Perception

To help bridge the gap between internet vision-style problems and the go...
04/06/2019 ∙ by Erik Wijmans, et al. ∙ 12 ∙ share

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Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning

Diverse and accurate vision+language modeling is an important goal to re...
08/22/2019 ∙ by Jyoti Aneja, et al. ∙ 12 ∙ share

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Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity

Spike-timing-dependent-plasticity (STDP) is an unsupervised learning alg...
09/11/2019 ∙ by Xueyuan She, et al. ∙ 12 ∙ share

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Grouped sparse projection

As evident from deep learning, very large models bring improvements in t...
12/09/2019 ∙ by Nicolas Gillis, et al. ∙ 12 ∙ share

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Robust, Extensible, and Fast: Teamed Classifiers for Vehicle Tracking in Multi-Camera Networks

As camera networks have become more ubiquitous over the past decade, the...
12/09/2019 ∙ by Abhijit Suprem, et al. ∙ 11 ∙ share

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Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Novel Dynamic Brush Model

Chinese calligraphy is a unique art form with great artistic value but d...
03/02/2020 ∙ by Sen Wang, et al. ∙ 11 ∙ share

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Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification

Recent advances in semi-supervised learning methods rely on estimating c...
06/12/2019 ∙ by Chia-Wen Kuo, et al. ∙ 10 ∙ share

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Looking GLAMORous: Vehicle Re-Id in Heterogeneous Cameras Networks with Global and Local Attention

Vehicle re-identification (re-id) is a fundamental problem for modern su...
02/06/2020 ∙ by Abhijit Suprem, et al. ∙ 10 ∙ share

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Cross-Layer Strategic Ensemble Defense Against Adversarial Examples

Deep neural network (DNN) has demonstrated its success in multiple domai...
10/01/2019 ∙ by Wenqi Wei, et al. ∙ 9 ∙ share

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Small, Accurate, and Fast Vehicle Re-ID on the Edge: the SAFR Approach

We propose a Small, Accurate, and Fast Re-ID (SAFR) design for flexible ...
01/24/2020 ∙ by Abhijit Suprem, et al. ∙ 9 ∙ share

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