118 citations · 300 across the 10 of their papers we have counts for
17 papers
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…
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…
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…
Learning Compressible 360° Video Isomers
Yu-Chuan Su, Kristen Grauman
Standard video encoders developed for conventional narrow field-of-view video are widely applied to 360° video as well, with reasonable results. However, while this approach commit…
Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks
Dinesh Jayaraman, Kristen Grauman
It is common to implicitly assume access to intelligently captured inputs (e.g., photos from a human photographer), yet autonomously capturing good observations is itself a major c…
Learning the Latent "Look": Unsupervised Discovery of a Style-Coherent Embedding from Fashion Images
Wei-Lin Hsiao, Kristen Grauman
What defines a visual style? Fashion styles emerge organically from how people assemble outfits of clothing, making them difficult to pin down with a computational model. Low-level…