Dhruv Mahajan

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What leads to generalization of object proposals?

Object proposal generation is often the first step in many detection mod...
08/13/2020 ∙ by Rui Wang, et al. ∙ 12 ∙ share

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Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias

Existing models often leverage co-occurrences between objects and their ...
01/09/2020 ∙ by Krishna Kumar Singh, et al. ∙ 32 ∙ share

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Measuring Dataset Granularity

Despite the increasing visibility of fine-grained recognition in our fie...
12/21/2019 ∙ by Yin Cui, et al. ∙ 54 ∙ share

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From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality

Blind or no-reference (NR) perceptual picture quality prediction is a di...
12/20/2019 ∙ by Zhenqiang Ying, et al. ∙ 13 ∙ share

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ClusterFit: Improving Generalization of Visual Representations

Pre-training convolutional neural networks with weakly-supervised and se...
12/06/2019 ∙ by Xueting Yan, et al. ∙ 0 ∙ share

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Self-Supervised Learning by Cross-Modal Audio-Video Clustering

The visual and audio modalities are highly correlated yet they contain d...
11/28/2019 ∙ by Humam Alwassel, et al. ∙ 25 ∙ share

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Scaling and Benchmarking Self-Supervised Visual Representation Learning

Self-supervised learning aims to learn representations from the data its...
05/03/2019 ∙ by Priya Goyal, et al. ∙ 0 ∙ share

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Large-scale weakly-supervised pre-training for video action recognition

Current fully-supervised video datasets consist of only a few hundred th...
05/02/2019 ∙ by Deepti Ghadiyaram, et al. ∙ 0 ∙ share

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Billion-scale semi-supervised learning for image classification

This paper presents a study of semi-supervised learning with large convo...
05/02/2019 ∙ by I. Zeki Yalniz, et al. ∙ 0 ∙ share

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Activity Driven Weakly Supervised Object Detection

Weakly supervised object detection aims at reducing the amount of superv...
04/02/2019 ∙ by Zhenheng Yang, et al. ∙ 0 ∙ share

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Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search

A plethora of recent work has shown that convolutional networks are not ...
03/05/2019 ∙ by Abhimanyu Dubey, et al. ∙ 0 ∙ share

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Exploring the Limits of Weakly Supervised Pretraining

State-of-the-art visual perception models for a wide range of tasks rely...
05/02/2018 ∙ by Dhruv Mahajan, et al. ∙ 0 ∙ share

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Distributed Newton Methods for Deep Neural Networks

Deep learning involves a difficult non-convex optimization problem with ...
02/01/2018 ∙ by Chien-Chih Wang, et al. ∙ 0 ∙ share

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Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles

For many applications, an ensemble of base classifiers is an effective s...
11/15/2017 ∙ by Dhruv Mahajan, et al. ∙ 0 ∙ share

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Towards Geo-Distributed Machine Learning

Latency to end-users and regulatory requirements push large companies to...
03/30/2016 ∙ by Ignacio Cano, et al. ∙ 0 ∙ share

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Dhruv Mahajan

Featured Co-authors

Rui Wang

Abhinav Gupta

Kristen Grauman

Bernard Ghanem

Serge Belongie

Ross Girshick

Kaiming He

Lorenzo Torresani

Hervé Jégou

Ram Nevatia

Laurens van der Maaten

What leads to generalization of object proposals?

Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias

Measuring Dataset Granularity

From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality

ClusterFit: Improving Generalization of Visual Representations

Self-Supervised Learning by Cross-Modal Audio-Video Clustering

Scaling and Benchmarking Self-Supervised Visual Representation Learning

Large-scale weakly-supervised pre-training for video action recognition

Billion-scale semi-supervised learning for image classification

Activity Driven Weakly Supervised Object Detection

Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search

Exploring the Limits of Weakly Supervised Pretraining

Distributed Newton Methods for Deep Neural Networks

Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles

Towards Geo-Distributed Machine Learning