MoViD disentangles motion and view features via a view estimator and orthogonal projection with contrastive alignment to deliver viewpoint-invariant 3D pose estimation that cuts errors over 24% with 60% less data and runs at 15 FPS on edge hardware.
and Ranjan, Vivek and Bhaduariya, Nirmednra , year =
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Generative AI suitability in qualitative research depends primarily on the approach (small-q positivist/post-positivist or Big Q non-positivist) along with skills, ethics, and personal preferences.
citing papers explorer
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MoViD: View-Invariant 3D Human Pose Estimation via Motion-View Disentanglement
MoViD disentangles motion and view features via a view estimator and orthogonal projection with contrastive alignment to deliver viewpoint-invariant 3D pose estimation that cuts errors over 24% with 60% less data and runs at 15 FPS on edge hardware.
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To Vibe Research or Not to Vibe Research? Generative AI in Qualitative Research
Generative AI suitability in qualitative research depends primarily on the approach (small-q positivist/post-positivist or Big Q non-positivist) along with skills, ethics, and personal preferences.