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Shape Anchors for Data-Driven Multi-View Reconstruction

This session presents "Shape Anchors for Data-Driven Multi-View Reconstruction," where researchers Andrew Owens, Jianxiong Xiao, Antonio Torralba, and William Freeman discuss innovative techniques in aligning sparse points using shape anchors. The method utilizes matches derived from an RGB-D database to improve the accuracy of multi-view reconstruction by effectively transferring good matches. The talk will delve into the implications of these advancements for future research in computer vision and reconstruction technologies, showcasing potential applications and theoretical underpinnings.

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Shape Anchors for Data-Driven Multi-View Reconstruction

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Presentation Transcript

  1. Poster Spotlights Session 1A: Tuesday Morning, December 3rd Shape Anchors for Data-driven Multi-view Reconstruction Andrew Owens Jianxiong Xiao Antonio Torralba William Freeman

  2. P1A-01 Shape Anchors for Data-driven Multi-view Reconstruction Align to sparse points Shape anchor Matches from RGB-D database Transfer good matches

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