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20152026
most citedUnsupervised Semantic Segmentation by Distilling Feature Correspondences

115 citations · 682 across the 61 of their papers we have counts for

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Showing 2021Show all

10 papers · 1 filter

cs.CV2021

Dimensions of Motion: Monocular Prediction through Flow Subspaces

Richard Strong Bowen, Richard Tucker, Ramin Zabih +1

We introduce a way to learn to estimate a scene representation from a single image by predicting a low-dimensional subspace of optical flow for each training example, which encompa…

cs.CV2021

Who's Waldo? Linking People Across Text and Images

Claire Yuqing Cui, Apoorv Khandelwal, Yoav Artzi +2

We present a task and benchmark dataset for person-centric visual grounding, the problem of linking between people named in a caption and people pictured in an image. In contrast t…

cs.CV2021

Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision

Xiaoshi Wu, Hadar Averbuch-Elor, Jin Sun +1

The abundance and richness of Internet photos of landmarks and cities has led to significant progress in 3D vision over the past two decades, including automated 3D reconstructions…

cs.CV2021

Wide-Baseline Relative Camera Pose Estimation with Directional Learning

Kefan Chen, Noah Snavely, Ameesh Makadia

Modern deep learning techniques that regress the relative camera pose between two images have difficulty dealing with challenging scenarios, such as large camera motions resulting…

cs.CV2021★ 3 cited

KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control

Tomas Jakab, Richard Tucker, Ameesh Makadia +3

We introduce KeypointDeformer, a novel unsupervised method for shape control through automatically discovered 3D keypoints. We cast this as the problem of aligning a source 3D obje…

cs.CV2021

Extreme Rotation Estimation using Dense Correlation Volumes

Ruojin Cai, Bharath Hariharan, Noah Snavely +1

We present a technique for estimating the relative 3D rotation of an RGB image pair in an extreme setting, where the images have little or no overlap. We observe that, even when im…