Paving the Way for Point Cloud Video Representation Learning Using A PDE Model | Paper Citation Record

Observation a36c45ce-bb4a-4f6d-bfbf-6adcd48c6af0 · outbound

This paper cites Self-scalable tanh (stan): Multi-scale solutions for physics- informed neural networks,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Self-scalable tanh (stan): Multi-scale solutions for physics- informed neural networks,

Reference 1

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Observation e472fd5f-17dd-4856-8a0d-58db9dad434d · outbound

This paper cites ClimODE: Climate and weather forecasting with physics-informed neural ODEs,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model ClimODE: Climate and weather forecasting with physics-informed neural ODEs,

Reference 2

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Observation 500aa0d7-91d7-4f5f-a915-22a739fbebed · outbound

This paper cites Available: https://openreview.net/forum?id= xuY33XhEGR.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Available: https://openreview.net/forum?id= xuY33XhEGR

Reference 3

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Observation c577712b-4e17-4c3d-a66d-85441f4a14ee · outbound

This paper cites Spectral neural operators,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Spectral neural operators,

Reference 4

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Observation 01f02e7b-ec33-4ca1-963b-0f0021d8fd44 · outbound

This paper cites Solving high- dimensional pdes with latent spectral models,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Solving high- dimensional pdes with latent spectral models,

Reference 5

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Observation 6f9c94fb-0279-4c47-8982-488e2702c991 · outbound

This paper cites HT-net: Hierarchical transformer based operator learning model for multiscale PDEs,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model HT-net: Hierarchical transformer based operator learning model for multiscale PDEs,

Reference 6

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Observation 6aef15f7-50cf-4821-849d-676ee26a6f37 · outbound

This paper cites Learning to diffuse: A new perspective to design pdes for visual analy- sis,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Learning to diffuse: A new perspective to design pdes for visual analy- sis,

Reference 7

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Observation 77165089-446b-435b-9fc0-ba3a8c04b902 · outbound

This paper cites Pde- constrained optimization in medical image analysis,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Pde- constrained optimization in medical image analysis,

Reference 8

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Observation ec94f43d-2d4c-46ff-85d7-7e61b07a8480 · outbound

This paper cites Formulating event-based image reconstruction as a linear inverse problem with deep regu- larization using optical flow,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Formulating event-based image reconstruction as a linear inverse problem with deep regu- larization using optical flow,

Reference 9

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Observation 13fae685-efe7-4cc3-bcb8-12e6e173ce65 · outbound

This paper cites Reformulating op- tical flow to solve image-based inverse problems and quantify uncertainty,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Reformulating op- tical flow to solve image-based inverse problems and quantify uncertainty,

Reference 10

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Observation 5e5e133b-472b-40ea-8f1a-fe788ce49997 · outbound

This paper cites Disentangling physical dynamics from unknown factors for unsupervised video prediction,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Disentangling physical dynamics from unknown factors for unsupervised video prediction,

Reference 11

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Observation 1e5d50b0-817c-4dea-893c-28bc060dba08 · outbound

This paper cites Disentangling stochastic pde dynamics for unsupervised video prediction,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Disentangling stochastic pde dynamics for unsupervised video prediction,

Reference 12

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Observation 7dad857a-c387-4943-b22b-44d673e9d250 · outbound

This paper cites PSTNet: Point spatio-temporal convolution on point cloud sequences,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model PSTNet: Point spatio-temporal convolution on point cloud sequences,

Reference 13

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Observation dbbbf951-df97-429e-b97f-f9baf3fcabd9 · outbound

This paper cites Learning representations and generative models for 3d point clouds,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Learning representations and generative models for 3d point clouds,

Reference 14

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Observation 202cface-c415-490e-8a57-23a8e03cc9a0 · outbound

This paper cites Foldingnet: Point cloud auto-encoder via deep grid deformation,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Foldingnet: Point cloud auto-encoder via deep grid deformation,

Reference 15

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Observation 2f230cab-745a-450a-9142-a6831c8689b0 · outbound

This paper cites Unsupervised learning of video representations using lstms,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Unsupervised learning of video representations using lstms,

Reference 16

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Observation 09e4b3a6-da89-4f04-975f-d69efb034d4d · outbound

This paper cites Optical flow guided feature: A fast and robust motion representation for video action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Optical flow guided feature: A fast and robust motion representation for video action recognition,

Reference 17

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Observation 7bcf12e8-683d-48c2-91b7-d2e4f50d1d00 · outbound

This paper cites Flow dynamics correction for action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Flow dynamics correction for action recognition,

Reference 18

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Observation 80b5b559-3f4d-45b2-8727-dc9c0fd6b01f · outbound

This paper cites Enhanced spatial stream of two-stream network using optical flow for human action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Enhanced spatial stream of two-stream network using optical flow for human action recognition,

Reference 19

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Observation ed0ca4ff-ebb2-4f74-b688-da1bab68364f · outbound

This paper cites Every frame counts: Joint learning of video segmentation and optical flow,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Every frame counts: Joint learning of video segmentation and optical flow,

Reference 20

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Observation 2bdba527-e3d2-4583-abfe-df6a2fbfbb71 · outbound

This paper cites Machine Learning for Partial Differential Equations.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Machine Learning for Partial Differential Equations

Reference 21

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Observation 1455db24-5b13-46c2-8d49-01247205ea3a · outbound

This paper cites Deep hierarchical representation of point cloud videos via spatio-temporal decom- position,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Deep hierarchical representation of point cloud videos via spatio-temporal decom- position,

Reference 22

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Observation b839ecd0-8a0d-465d-8827-65e923b87c87 · outbound

This paper cites Point 4d transformer networks for spatio-temporal modeling in point cloud videos,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Point 4d transformer networks for spatio-temporal modeling in point cloud videos,

Reference 23

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Observation b3aabbf3-2170-43e1-bc0a-fd969a90bea7 · outbound

This paper cites Point spatio-temporal transformer networks for point cloud video modeling,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Point spatio-temporal transformer networks for point cloud video modeling,

Reference 24

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Observation 1391b5ab-67d9-41cf-9856-041111263610 · outbound

This paper cites No pain, big gain: Classify dynamic point cloud sequences with static models by fitting feature-level space-time surfaces,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model No pain, big gain: Classify dynamic point cloud sequences with static models by fitting feature-level space-time surfaces,

Reference 25

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Observation c81749fd-ba05-437a-87d7-a8b90f24d202 · outbound

This paper cites Geometrymotion-net: A strong two-stream baseline for 3d action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Geometrymotion-net: A strong two-stream baseline for 3d action recognition,

Reference 26

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Observation 82218286-e151-4b42-9e5d-ccd57c51f29b · outbound

This paper cites Geometrymotion-transformer: An end- to-end framework for 3d action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Geometrymotion-transformer: An end- to-end framework for 3d action recognition,

Reference 27

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Observation 83d7361c-499f-4179-baae-98d7cb858ab6 · outbound

This paper cites an unresolved cited work.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Unresolved cited work

Reference 28

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Observation 0d274488-6a16-4b3a-a320-79daa267e0ff · outbound

This paper cites Pde-based progres- sive prediction framework for attribute compression of 3d point clouds,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Pde-based progres- sive prediction framework for attribute compression of 3d point clouds,

Reference 29

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Observation 56eee0ad-6d1c-4c28-86a8-e7d739f89dd9 · outbound

This paper cites Gottlieb and S.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Gottlieb and S

Reference 30

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Observation af2d90d3-25ae-4ebc-b761-717f01bdd057 · outbound

This paper cites Fornberg,A practical guide to pseudospectral methods.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Fornberg,A practical guide to pseudospectral methods

Reference 31

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Observation 9db35026-277e-4036-9d39-95c6c33aca90 · outbound

This paper cites ˆSol´ın,Partial differential equations and the finite element method.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model ˆSol´ın,Partial differential equations and the finite element method

Reference 32

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Observation f682232d-65aa-4800-9877-fa9b83fbcf93 · outbound

This paper cites Grossmann,Numerical treatment of partial differential equations.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Grossmann,Numerical treatment of partial differential equations

Reference 33

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Observation 05c43f91-9006-42f1-afd3-e93a6c2f9c63 · outbound

This paper cites The deep ritz method: a deep learning-based numer- ical algorithm for solving variational problems,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model The deep ritz method: a deep learning-based numer- ical algorithm for solving variational problems,

Reference 34

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Observation 373a2d44-9d02-4c6e-93a7-19c2d8943f34 · outbound

This paper cites A deep learning framework for solv- ing forward and inverse problems of power-law fluids,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model A deep learning framework for solv- ing forward and inverse problems of power-law fluids,

Reference 35

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Observation ff361b1c-428b-4b0e-b688-b732585637f0 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Fourier Neural Operator for Parametric Partial Differential Equations

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-01T21:56:16.452573Z

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Observation f202891b-61b3-47ef-8f84-23a7c6956063 · outbound

This paper cites Factorized fourier neural operators,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Factorized fourier neural operators,

Reference 37

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This paper cites Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net,

Reference 38

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Observation ae6fab1a-429a-453c-90d1-81d0e2847bec · outbound

This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model 4d spatio-temporal convnets: Minkowski convolutional neural networks,

Reference 39

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Observation 366aeeba-1ec3-46e0-8fd6-fde2fbd6decd · outbound

This paper cites 3dv: 3d dynamic voxel for action recognition in depth video,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model 3dv: 3d dynamic voxel for action recognition in depth video,

Reference 40

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Observation 00b3c0c6-3dd2-4ca9-9a40-6a8b90ba2331 · outbound

This paper cites Meteornet: Deep learning on dynamic 3d point cloud sequences,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Meteornet: Deep learning on dynamic 3d point cloud sequences,

Reference 41

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Observation 7fdd9c2f-2d20-4654-9544-a91bfa0e27e9 · outbound

This paper cites An efficient pointlstm for point clouds based gesture recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model An efficient pointlstm for point clouds based gesture recognition,

Reference 42

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Observation d0b272fc-cdc7-460d-9db9-21941ec11151 · outbound

This paper cites Pointnet++: Deep hierar- chical feature learning on point sets in a metric space,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Pointnet++: Deep hierar- chical feature learning on point sets in a metric space,

Reference 43

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Observation cfc81b20-2a89-4605-bb2c-b6b4b5ed78ff · outbound

This paper cites Pref: Predictability regularized neural mo- tion fields,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Pref: Predictability regularized neural mo- tion fields,

Reference 44

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Observation 73f24d07-99b0-477d-8366-34f14ce20921 · outbound

This paper cites Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems,

Reference 45

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Observation 1be1d41c-8a82-4115-a807-4dcc5db30291 · outbound

This paper cites Physics-informed machine learning,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Physics-informed machine learning,

Reference 46

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Observation 14b85e78-a6b2-49b7-a5d7-c8db760d3430 · outbound

This paper cites Learning nonlinear operators via deeponet based on the universal approx- imation theorem of operators,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Learning nonlinear operators via deeponet based on the universal approx- imation theorem of operators,

Reference 47

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Observation 845e74ac-6431-46ba-a109-601ff5b81752 · outbound

This paper cites Fourier neural operator for parametric partial differential equations,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Fourier neural operator for parametric partial differential equations,

Reference 48

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Observation e8f4b4cf-57e1-4b40-a779-b132113a2b3c · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Representation Learning with Contrastive Predictive Coding

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-07-01T21:56:16.455122Z

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Observation 2e68e8b4-011e-4102-aab5-1db83fb5a4fb · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model A simple framework for contrastive learning of visual representations,

Reference 50

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Observation ffe1c768-2ee6-422a-8fd2-1cdf9b57fe31 · outbound

This paper cites Pointmapnet: Point cloud feature map network for 3d human action IEEE TRANSACTIONS ON PATTERN ANAL YSIS AND MACHINE INTELLIGENCE 17 recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Pointmapnet: Point cloud feature map network for 3d human action IEEE TRANSACTIONS ON PATTERN ANAL YSIS AND MACHINE INTELLIGENCE 17 recognition,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation eb70bffc-dff0-4f7c-b200-90dff56942e8 · outbound

This paper cites Real-time 3-d human action recognition based on hyperpoint sequence,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Real-time 3-d human action recognition based on hyperpoint sequence,

Reference 52

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Observation 90a7a9c8-dedf-4ce0-8de2-d20463c744c3 · outbound

This paper cites 3DInAction: Understanding Human Actions in 3D Point Clouds.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model 3DInAction: Understanding Human Actions in 3D Point Clouds

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:56:16.457947Z

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Observation c3a5d901-dd70-426f-99f7-01436ddbc116 · outbound

This paper cites Hyperpointnet for point cloud sequence-based 3d human action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Hyperpointnet for point cloud sequence-based 3d human action recognition,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation 25414a8b-68e2-42ec-ad0e-054fafaf8707 · outbound

This paper cites Point primitive transformer for long-term 4d point cloud video understanding,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Point primitive transformer for long-term 4d point cloud video understanding,

Reference 55

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Observation 2fdb5f84-4bd6-4c93-971e-9c55442ca32c · outbound

This paper cites Point contrastive prediction with semantic clustering for self-supervised learning on point cloud videos,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Point contrastive prediction with semantic clustering for self-supervised learning on point cloud videos,

Reference 56

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Observation 40a4ed6d-f0f9-4b07-91a7-c78bb6b00427 · outbound

This paper cites Mamba4d: Efficient 4d point cloud video understand- ing with disentangled spatial-temporal state space models,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Mamba4d: Efficient 4d point cloud video understand- ing with disentangled spatial-temporal state space models,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation ec1bce8a-9d39-4144-98ce-ccb261060c19 · outbound

This paper cites Kan- hyperpointnet for point cloud sequence-based 3d human action recognition,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Kan- hyperpointnet for point cloud sequence-based 3d human action recognition,

Reference 58

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Observation 25abf358-d37a-4161-bb6c-77dc88d0235d · outbound

This paper cites Action recognition based on a bag of 3d points,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Action recognition based on a bag of 3d points,

Reference 59

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Observation 47930eb6-f01b-495a-90f9-a86b0b57d164 · outbound

This paper cites Ntu rgb+ d: A large scale dataset for 3d human activity analysis,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Ntu rgb+ d: A large scale dataset for 3d human activity analysis,

Reference 60

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Observation 04c91e53-3ed8-4b76-a687-cdb4bd3e3726 · outbound

This paper cites Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation 9c438c24-fb9c-49a4-8e9e-e077f748eb28 · outbound

This paper cites Utd-mhad: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Utd-mhad: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation 14cb0dc9-0119-4d05-b5e3-ade82eb9c8a3 · outbound

This paper cites Hoi4d: A 4d egocentric dataset for category- level human-object interaction,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Hoi4d: A 4d egocentric dataset for category- level human-object interaction,

Reference 63

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Observation dc47eba3-0396-4211-8f7d-25c2b436de3b · outbound

This paper cites Shrec’17 track: 3d hand gesture recognition using a depth and skeletal dataset,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Shrec’17 track: 3d hand gesture recognition using a depth and skeletal dataset,

Reference 64

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Observation 325a6072-711b-468a-bd31-acd252382a11 · outbound

This paper cites Leaf: Learning frames for 4d point cloud sequence understanding,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Leaf: Learning frames for 4d point cloud sequence understanding,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation 1e430fe0-5c78-416c-b679-a6698b385eba · outbound

This paper cites X4d-sceneformer: Enhanced scene understanding on 4d point cloud videos through cross-modal knowledge transfer,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model X4d-sceneformer: Enhanced scene understanding on 4d point cloud videos through cross-modal knowledge transfer,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation 43cc9753-48b7-40bb-8a6a-8942630c13f4 · outbound

This paper cites Complete-to-partial 4d dis- tillation for self-supervised point cloud sequence representation learning,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Complete-to-partial 4d dis- tillation for self-supervised point cloud sequence representation learning,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-28T15:54:20.884536Z

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Observation 6f830c40-b175-479e-86f7-881254aa579b · outbound

This paper cites Ms-tcn: Multi-stage temporal convo- lutional network for action segmentation,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Ms-tcn: Multi-stage temporal convo- lutional network for action segmentation,

Reference 68

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Observation ba8cf63c-8452-4345-8de6-f3cac0298133 · outbound

This paper cites Ms-tcn++: Multi-stage temporal convolutional network for action segmenta- tion,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Ms-tcn++: Multi-stage temporal convolutional network for action segmenta- tion,

Reference 69

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Observation c00c1153-f505-4c44-bd30-878db6a41379 · outbound

This paper cites Asformer: Transformer for action segmentation,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Asformer: Transformer for action segmentation,

Reference 70

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Observation c2dee91e-d456-434d-ab3d-630105d13787 · outbound

This paper cites Pointnetlk: Robust & efficient point cloud registration using pointnet,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Pointnetlk: Robust & efficient point cloud registration using pointnet,

Reference 71

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Observation c233b9c8-c7b8-4041-8631-6c4911b6b006 · outbound

This paper cites Benchmarking and improving robustness of 3d point cloud recognition against common corruptions,.

Paving the Way for Point Cloud Video Representation Learning Using A PDE Model Benchmarking and improving robustness of 3d point cloud recognition against common corruptions,

Reference 72

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