• Publications
  • Influence
Microsoft COCO: Common Objects in Context
TLDR
We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. Expand
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SUN database: Large-scale scene recognition from abbey to zoo
TLDR
We propose the extensive Scene UNderstanding (SUN) database that contains 899 categories and 130,519 images. Expand
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SUN attribute database: Discovering, annotating, and recognizing scene attributes
TLDR
We present the first large-scale scene attribute database and train attribute classifiers on top of it. Expand
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How do humans sketch objects?
TLDR
This paper is the first large scale exploration of human sketches. Expand
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IM2GPS: estimating geographic information from a single image
TLDR
We propose an algorithm for estimating a distribution over geographic locations from a single image using a purely data-driven scene matching approach. Expand
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The sketchy database
TLDR
The Sketchy database gives us fine-grained associations between particular photos and sketches, and we use this to train cross-domain convolutional networks which embed sketches and photographs in a common feature space. Expand
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The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding
In this paper we present the first large-scale scene attribute database. First, we perform crowdsourced human studies to find a taxonomy of 102 discriminative attributes. We discover attributesExpand
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Edge-based blur kernel estimation using patch priors
TLDR
We introduce a new patch-based strategy for kernel estimation in blind deconvolution by imposing a patch prior specifically tailored towards modeling the appearance of image edge and corner primitives. Expand
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Argoverse: 3D Tracking and Forecasting With Rich Maps
TLDR
We present Argoverse, a dataset designed to support autonomous vehicle perception tasks including 3D tracking and motion forecasting. Expand
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Scene completion using millions of photographs
TLDR
We present a new image completion algorithm powered by a huge database of photographs gathered from the Web. Expand
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