Marcus Rohrbach

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berkeley college

Research scientist at Facebook AI Research

Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering

We propose a new class of probabilistic neural-symbolic models, that hav...
02/21/2019 ∙ by Ramakrishna Vedantam, et al. ∙ 24 ∙ share

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Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA

Many visual scenes contain text that carries crucial information, and it...
11/14/2019 ∙ by Ronghang Hu, et al. ∙ 22 ∙ share

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12-in-1: Multi-Task Vision and Language Representation Learning

Much of vision-and-language research focuses on a small but diverse set ...
12/05/2019 ∙ by Jiasen Lu, et al. ∙ 22 ∙ 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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Adversarial Inference for Multi-Sentence Video Description

While significant progress has been made in the image captioning task, v...
12/13/2018 ∙ by Jae Sung Park, et al. ∙ 14 ∙ 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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Pythia v0.1: the Winning Entry to the VQA Challenge 2018

This document describes Pythia v0.1, the winning entry from Facebook AI ...
07/26/2018 ∙ by Yu Jiang, et al. ∙ 12 ∙ share

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Towards VQA Models that can Read

Studies have shown that a dominant class of questions asked by visually ...
04/18/2019 ∙ by Amanpreet Singh, et al. ∙ 12 ∙ share

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Grounded Video Description

Video description is one of the most challenging problems in vision and ...
12/17/2018 ∙ by Luowei Zhou, et al. ∙ 8 ∙ share

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Adversarial Continual Learning

Continual learning aims to learn new tasks without forgetting previously...
03/21/2020 ∙ by Sayna Ebrahimi, et al. ∙ 8 ∙ share

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In Defense of Grid Features for Visual Question Answering

Popularized as 'bottom-up' attention, bounding box (or region) based vis...
01/10/2020 ∙ by Huaizu Jiang, et al. ∙ 7 ∙ share

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Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Deep models that are both effective and explainable are desirable in man...
02/15/2018 ∙ by Dong Huk Park, et al. ∙ 1 ∙ share

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Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)

Deep models are the defacto standard in visual decision problems due to ...
11/17/2017 ∙ by Dong Huk Park, et al. ∙ 0 ∙ share

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Generating Descriptions with Grounded and Co-Referenced People

Learning how to generate descriptions of images or videos received major...
04/05/2017 ∙ by Anna Rohrbach, et al. ∙ 0 ∙ share

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Modeling Relationships in Referential Expressions with Compositional Modular Networks

People often refer to entities in an image in terms of their relationshi...
11/30/2016 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions

Image segmentation from referring expressions is a joint vision and lang...
08/30/2016 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Segmentation from Natural Language Expressions

In this paper we approach the novel problem of segmenting an image based...
03/20/2016 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Spatial Semantic Regularisation for Large Scale Object Detection

Large scale object detection with thousands of classes introduces the pr...
10/10/2015 ∙ by Damian Mrowca, et al. ∙ 0 ∙ share

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The Long-Short Story of Movie Description

Generating descriptions for videos has many applications including assis...
06/04/2015 ∙ by Anna Rohrbach, et al. ∙ 0 ∙ share

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Sequence to Sequence -- Video to Text

Real-world videos often have complex dynamics; and methods for generatin...
05/03/2015 ∙ by Subhashini Venugopalan, et al. ∙ 0 ∙ share

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Recognizing Fine-Grained and Composite Activities using Hand-Centric Features and Script Data

Activity recognition has shown impressive progress in recent years. Howe...
02/23/2015 ∙ by Marcus Rohrbach, et al. ∙ 0 ∙ share

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Long-term Recurrent Convolutional Networks for Visual Recognition and Description

Models based on deep convolutional networks have dominated recent image ...
11/17/2014 ∙ by Jeff Donahue, et al. ∙ 0 ∙ share

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Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training

While strong progress has been made in image captioning over the last ye...
03/30/2017 ∙ by Rakshith Shetty, et al. ∙ 0 ∙ share

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Attentive Explanations: Justifying Decisions and Pointing to the Evidence

Deep models are the defacto standard in visual decision models due to th...
12/14/2016 ∙ by Dong Huk Park, et al. ∙ 0 ∙ share

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Captioning Images with Diverse Objects

Recent captioning models are limited in their ability to scale and descr...
06/24/2016 ∙ by Subhashini Venugopalan, et al. ∙ 0 ∙ share

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Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding

Modeling textual or visual information with vector representations train...
06/06/2016 ∙ by Akira Fukui, et al. ∙ 0 ∙ share

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Movie Description

Audio Description (AD) provides linguistic descriptions of movies and al...
05/12/2016 ∙ by Anna Rohrbach, et al. ∙ 0 ∙ share

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Ask Your Neurons: A Deep Learning Approach to Visual Question Answering

We address a question answering task on real-world images that is set up...
05/09/2016 ∙ by Mateusz Malinowski, et al. ∙ 0 ∙ share

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Attributes as Semantic Units between Natural Language and Visual Recognition

Impressive progress has been made in the fields of computer vision and n...
04/12/2016 ∙ by Marcus Rohrbach, et al. ∙ 0 ∙ share

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Generating Visual Explanations

Clearly explaining a rationale for a classification decision to an end-u...
03/28/2016 ∙ by Lisa Anne Hendricks, et al. ∙ 0 ∙ share

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Learning to Compose Neural Networks for Question Answering

We describe a question answering model that applies to both images and s...
01/07/2016 ∙ by Jacob Andreas, et al. ∙ 0 ∙ share

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Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data

While recent deep neural network models have achieved promising results ...
11/17/2015 ∙ by Lisa Anne Hendricks, et al. ∙ 0 ∙ share

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Natural Language Object Retrieval

In this paper, we address the task of natural language object retrieval,...
11/13/2015 ∙ by Ronghang Hu, et al. ∙ 0 ∙ share

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Grounding of Textual Phrases in Images by Reconstruction

Grounding (i.e. localizing) arbitrary, free-form textual phrases in visu...
11/12/2015 ∙ by Anna Rohrbach, et al. ∙ 0 ∙ share

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Neural Module Networks

Visual question answering is fundamentally compositional in nature---a q...
11/09/2015 ∙ by Jacob Andreas, et al. ∙ 0 ∙ share

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Ask Your Neurons: A Neural-based Approach to Answering Questions about Images

We address a question answering task on real-world images that is set up...
05/05/2015 ∙ by Mateusz Malinowski, et al. ∙ 0 ∙ share

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A Dataset for Movie Description

Descriptive video service (DVS) provides linguistic descriptions of movi...
01/12/2015 ∙ by Anna Rohrbach, et al. ∙ 0 ∙ share

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Translating Videos to Natural Language Using Deep Recurrent Neural Networks

Solving the visual symbol grounding problem has long been a goal of arti...
12/15/2014 ∙ by Subhashini Venugopalan, et al. ∙ 0 ∙ share

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Memory Aware Synapses: Learning what (not) to forget

Humans can learn in a continuous manner. Old rarely utilized knowledge c...
11/27/2017 ∙ by Rahaf Aljundi, et al. ∙ 0 ∙ share

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Large-Scale Visual Relationship Understanding

Large scale visual understanding is challenging, as it requires a model ...
04/27/2018 ∙ by Ji Zhang, et al. ∙ 0 ∙ share

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Selfless Sequential Learning

Sequential learning studies the problem of learning tasks in a sequence ...
06/14/2018 ∙ by Rahaf Aljundi, et al. ∙ 0 ∙ share

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Visual Coreference Resolution in Visual Dialog using Neural Module Networks

Visual dialog entails answering a series of questions grounded in an ima...
09/06/2018 ∙ by Satwik Kottur, et al. ∙ 0 ∙ share

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Graph-Based Global Reasoning Networks

Globally modeling and reasoning over relations between regions can be be...
11/30/2018 ∙ by Yunpeng Chen, et al. ∙ 0 ∙ share

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Efficient Lifelong Learning with A-GEM

In lifelong learning, the learner is presented with a sequence of tasks,...
12/02/2018 ∙ by Arslan Chaudhry, et al. ∙ 0 ∙ share

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Exploring the Challenges towards Lifelong Fact Learning

So far life-long learning (LLL) has been studied in relatively small-sca...
12/26/2018 ∙ by Mohamed Elhoseiny, et al. ∙ 0 ∙ share

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DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition

Motion has shown to be useful for video understanding, where motion is t...
01/11/2019 ∙ by Zheng Shou, et al. ∙ 0 ∙ share

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Continual Learning with Tiny Episodic Memories

Learning with less supervision is a major challenge in artificial intell...
02/27/2019 ∙ by Arslan Chaudhry, et al. ∙ 0 ∙ share

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Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

In natural images, information is conveyed at different frequencies wher...
04/10/2019 ∙ by Yunpeng Chen, et al. ∙ 0 ∙ share

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Learning to Generate Grounded Image Captions without Localization Supervision

When generating a sentence description for an image, it frequently remai...
06/01/2019 ∙ by Chih-Yao Ma, et al. ∙ 0 ∙ share

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Uncertainty-guided Continual Learning with Bayesian Neural Networks

Continual learning aims to learn new tasks without forgetting previously...
06/06/2019 ∙ by Sayna Ebrahimi, et al. ∙ 0 ∙ share

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Marcus Rohrbach

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