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Intrinsic Geometry Meets Deep Learning: A Riemannian Manifold and Lstm Framework for Robust Human Motion Modeling

https://doi.org/10.2139/ssrn.4528508
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8/8 checkable references clean · checked 2026-09-05

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

17 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 8 checked references that resolve
resolves10.1145/2766999
Realtime style transfer for unlabeled heterogeneous human motion
resolves10.1109/TPAMI.2007.1167
Gaussian Process Dynamical Models for Human Motion
resolves10.1109/TPAMI.2019.2896631
View Adaptive Neural Networks for High Performance Skeleton-Based Human Action Recognition
resolves10.1016/j.patcog.2017.02.030
Enhanced skeleton visualization for view invariant human action recognition
resolves10.1145/1599470.1599473
Efficient and robust annotation of motion capture data
resolves10.1109/TIP.2018.2818328
Spatio-Temporal Attention-Based LSTM Networks for 3D Action Recognition and Detection
resolves10.1145/2897824.2925975
A deep learning framework for character motion synthesis and editing
resolves10.1109/TPAMI.2015.2414422
Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels
The 17 references without a DOI — listed, not checked
no DOI — not checkedref1
no DOI — not checkedDeriving action and behavior primitives from human motion data
no DOI — not checkedHuman action recognition by representing 3D skeletons as points in a Lie group
no DOI — not checkedView invariant human action recognition using histograms of 3D joints
no DOI — not checkedHierarchical recurrent neural network for skeleton based action recognition
no DOI — not checkedA real-time annotation of motion data streams
no DOI — not checkedAnalyzing the physical correctness of interpolated human motion
no DOI — not checkedref13
no DOI — not checkedref15
no DOI — not checkedMotion capture data segmentation using Riemannian manifold learning
no DOI — not checkedSee, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion
no DOI — not checkedSpatial temporal graph convolutional networks for skeleton-based action recognition
no DOI — not checkedSkeleton-based action recognition with directed graph neural networks
no DOI — not checkedSpatio-temporal LSTM with trust gates for 3D human action recognition
no DOI — not checkedDeep learning on Lie groups for skeleton-based action recognition
no DOI — not checkedref24
no DOI — not checkedref25
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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