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Understanding 3D Object Articulation in Internet Videos

About

We propose to investigate detecting and characterizing the 3D planar articulation of objects from ordinary videos. While seemingly easy for humans, this problem poses many challenges for computers. We propose to approach this problem by combining a top-down detection system that finds planes that can be articulated along with an optimization approach that solves for a 3D plane that can explain a sequence of observed articulations. We show that this system can be trained on a combination of videos and 3D scan datasets. When tested on a dataset of challenging Internet videos and the Charades dataset, our approach obtains strong performance. Project site: https://jasonqsy.github.io/Articulation3D

Shengyi Qian, Linyi Jin, Chris Rockwell, Siyi Chen, David F. Fouhey• 2022

Related benchmarks

TaskDatasetResultRank
Rotation Articulation DescriptionInternet videos
AP (bbox+axis)30.4
5
Translation Articulation DescriptionInternet videos
AP (bbox+axis)27.1
5
3D Articulation Rotation EstimationCharades 52 (test)
AP (bbox+axis)12.8
5
Articulation EstimationHD-EPIC 64 (test)
Match (%)42.22
5
Articulation EstimationArti4D 82 (test)
Match Rate (%)84.29
4
Articulation RecognitionInternet videos
AUROC76.6
3
Articulation RecognitionCharades 52 (test)
AUROC58.4
3
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