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20142026
most citedZero Shot Recognition with Unreliable Attributes

175 citations · 1.9k across the 98 of their papers we have counts for

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Showing 2019 · cs.CVShow all

13 papers · 2 filters

cs.CV2019★ 7 cited

SoundSpaces: Audio-Visual Navigation in 3D Environments

Changan Chen, Unnat Jain, Carl Schissler +5

Moving around in the world is naturally a multisensory experience, but today's embodied agents are deaf---restricted to solely their visual perception of the environment. We introd…

cs.CV2019

ViBE: Dressing for Diverse Body Shapes

Wei-Lin Hsiao, Kristen Grauman

Body shape plays an important role in determining what garments will best suit a given person, yet today's clothing recommendation methods take a "one shape fits all" approach. The…

cs.CV2019★ 10 cited

Listen to Look: Action Recognition by Previewing Audio

Ruohan Gao, Tae-Hyun Oh, Kristen Grauman +1

In the face of the video data deluge, today's expensive clip-level classifiers are increasingly impractical. We propose a framework for efficient action recognition in untrimmed vi…

cs.CV2019★ 38 cited

Emergence of Exploratory Look-Around Behaviors through Active Observation Completion

Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman

Standard computer vision systems assume access to intelligently captured inputs (e.g., photos from a human photographer), yet autonomously capturing good observations is a major ch…

cs.CV2019

Grounded Human-Object Interaction Hotspots from Video (Extended Abstract)

Tushar Nagarajan, Christoph Feichtenhofer, Kristen Grauman

Learning how to interact with objects is an important step towards embodied visual intelligence, but existing techniques suffer from heavy supervision or sensing requirements. We p…

cs.CV2019

Predicting How to Distribute Work Between Algorithms and Humans to Segment an Image Batch

Danna Gurari, Yinan Zhao, Suyog Dutt Jain +2

Foreground object segmentation is a critical step for many image analysis tasks. While automated methods can produce high-quality results, their failures disappoint users in need o…