Olga Russakovsky

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Princeton University ∙ Carnegie Mellon University ∙ Stanford University

Assistant Professor Department of Computer Science at Princeton University

CornerNet-Lite: Efficient Keypoint Based Object Detection

Keypoint-based methods are a relatively new paradigm in object detection...
04/18/2019 ∙ by Hei Law, et al. ∙ 20 ∙ share

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Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy

Computer vision technology is being used by many but remains representat...
12/16/2019 ∙ by Kaiyu Yang, et al. ∙ 9 ∙ share

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Compositional Temporal Visual Grounding of Natural Language Event Descriptions

Temporal grounding entails establishing a correspondence between natural...
12/04/2019 ∙ by Jonathan C. Stroud, et al. ∙ 6 ∙ share

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SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition

Understanding the spatial relations between objects in images is a surpr...
08/07/2019 ∙ by Kaiyu Yang, et al. ∙ 1 ∙ share

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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...
11/22/2015 ∙ by Serena Yeung, et al. ∙ 0 ∙ share

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What's in a Question: Using Visual Questions as a Form of Supervision

Collecting fully annotated image datasets is challenging and expensive. ...
04/12/2017 ∙ by Siddha Ganju, et al. ∙ 0 ∙ share

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Predictive-Corrective Networks for Action Detection

While deep feature learning has revolutionized techniques for static-ima...
04/12/2017 ∙ by Achal Dave, et al. ∙ 0 ∙ share

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What Actions are Needed for Understanding Human Actions in Videos?

What is the right way to reason about human activities? What directions ...
08/09/2017 ∙ by Gunnar A. Sigurdsson, et al. ∙ 0 ∙ share

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Learning to Learn from Noisy Web Videos

Understanding the simultaneously very diverse and intricately fine-grain...
06/09/2017 ∙ by Serena Yeung, et al. ∙ 0 ∙ share

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Crowdsourcing in Computer Vision

Computer vision systems require large amounts of manually annotated data...
11/07/2016 ∙ by Adriana Kovashka, et al. ∙ 0 ∙ share

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Much Ado About Time: Exhaustive Annotation of Temporal Data

Large-scale annotated datasets allow AI systems to learn from and build ...
07/25/2016 ∙ by Gunnar A. Sigurdsson, et al. ∙ 0 ∙ share

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

Every moment counts in action recognition. A comprehensive understanding...
07/21/2015 ∙ by Serena Yeung, et al. ∙ 0 ∙ share

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What's the Point: Semantic Segmentation with Point Supervision

The semantic image segmentation task presents a trade-off between test t...
06/06/2015 ∙ by Amy Bearman, et al. ∙ 0 ∙ share

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Joint calibration of Ensemble of Exemplar SVMs

We present a method for calibrating the Ensemble of Exemplar SVMs model....
03/02/2015 ∙ by Davide Modolo, et al. ∙ 0 ∙ share

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ImageNet Large Scale Visual Recognition Challenge

The ImageNet Large Scale Visual Recognition Challenge is a benchmark in ...
09/01/2014 ∙ by Olga Russakovsky, et al. ∙ 0 ∙ share

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Human uncertainty makes classification more robust

The classification performance of deep neural networks has begun to asym...
08/19/2019 ∙ by Joshua C. Peterson, et al. ∙ 0 ∙ share

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Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation

Computer vision models learn to perform a task by capturing relevant sta...
11/26/2019 ∙ by Zeyu Wang, et al. ∙ 0 ∙ share

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Olga Russakovsky

Featured Co-authors

Li Fei-Fei

Abhinav Gupta

Ali Farhadi

Kristen Grauman

Hao Su

Deva Ramanan

Vittorio Ferrari

Greg Mori

Jia Deng

Ivan Laptev

Thomas L. Griffiths

CornerNet-Lite: Efficient Keypoint Based Object Detection

Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy

Compositional Temporal Visual Grounding of Natural Language Event Descriptions

SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition

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

What's in a Question: Using Visual Questions as a Form of Supervision

Predictive-Corrective Networks for Action Detection

What Actions are Needed for Understanding Human Actions in Videos?

Learning to Learn from Noisy Web Videos

Crowdsourcing in Computer Vision

Much Ado About Time: Exhaustive Annotation of Temporal Data

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

What's the Point: Semantic Segmentation with Point Supervision

Joint calibration of Ensemble of Exemplar SVMs

ImageNet Large Scale Visual Recognition Challenge

Human uncertainty makes classification more robust

Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation