Paper Citation Record · LEDGER

Learning Normal Flow Directly From Event Neighborhoods

As of 13 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 4 inbound Pith citation observations for arXiv:2412.11284.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.11284 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:13:23.293780Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:35:26.587738Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T14:14:45.635113Z

Reference resolution

72 of 72 outbound references displayed

verified exact7
verified fuzzy49
unresolved15
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e9e6f62-941d-41d2-b138-a0aec3f04a73 · outbound

This paper cites https://docs.scipy.org/doc/ scipy / reference / generated / scipy.

Learning Normal Flow Directly From Event Neighborhoods https://docs.scipy.org/doc/ scipy / reference / generated / scipy

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.881363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 580315c9-5847-41e0-a7ff-060af917b276 · outbound

This paper cites https : / / elvers.

Learning Normal Flow Directly From Event Neighborhoods https : / / elvers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.873595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b72f2f64-e5bb-4752-a46d-dd996e364083 · outbound

This paper cites Real-time high speed motion prediction using fast aperture- robust event-driven visual flow.

Learning Normal Flow Directly From Event Neighborhoods Real-time high speed motion prediction using fast aperture- robust event-driven visual flow

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.866909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 38858529-ac8a-4443-90a9-7edcc4261828 · outbound

This paper cites Distance surface for event- based optical flow.

Learning Normal Flow Directly From Event Neighborhoods Distance surface for event- based optical flow

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.859957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dd3f7c3c-d8b1-4007-9b1a-a88e7c8c1f81 · outbound

This paper cites Contour motion estimation for asynchronous event- driven cameras.

Learning Normal Flow Directly From Event Neighborhoods Contour motion estimation for asynchronous event- driven cameras

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.853235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ef67800a-9d7c-4b58-9605-ca1cd88727a7 · outbound

This paper cites Bio-inspired motion estimation with event-driven sensors.

Learning Normal Flow Directly From Event Neighborhoods Bio-inspired motion estimation with event-driven sensors

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.845668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3e2d67ff-5525-4c5a-9681-0fbc4987949a · outbound

This paper cites Joint direct estimation of 3d geometry and 3d motion using spatio temporal gradients.

Learning Normal Flow Directly From Event Neighborhoods Joint direct estimation of 3d geometry and 3d motion using spatio temporal gradients

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.838571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 04074efe-8dcb-431e-a825-071921606f3c · outbound

This paper cites Asynchronous frameless event-based optical flow.

Learning Normal Flow Directly From Event Neighborhoods Asynchronous frameless event-based optical flow

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.831177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0eb8718c-67e1-4d56-9ffd-05c784bdb931 · outbound

This paper cites Event-based visual flow.

Learning Normal Flow Directly From Event Neighborhoods Event-based visual flow

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.823825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8f90bee5-4230-4278-b150-cd4d73d5118e · outbound

This paper cites Real- time optical flow for vehicular perception with low-and high- resolution event cameras.

Learning Normal Flow Directly From Event Neighborhoods Real- time optical flow for vehicular perception with low-and high- resolution event cameras

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.816927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b7d25564-c715-44bf-9ba7-7f0748093648 · outbound

This paper cites Structure from motion: Beyond the epipolar con- straint.

Learning Normal Flow Directly From Event Neighborhoods Structure from motion: Beyond the epipolar con- straint

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.809671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2e8d9379-7e7a-4eb5-8c0d-7efbfbf0ecfd · outbound

This paper cites On event-based optical flow detection.

Learning Normal Flow Directly From Event Neighborhoods On event-based optical flow detection

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.801528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c843aa9b-2c3a-4688-a2ba-8ac028d43329 · outbound

This paper cites EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms.

Learning Normal Flow Directly From Event Neighborhoods EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.106736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e3a8806-d54e-40bc-8f72-b7489860d6e0 · outbound

This paper cites Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation.

Learning Normal Flow Directly From Event Neighborhoods Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.436924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 36dbd645-3304-4746-a11d-d2099f986168 · outbound

This paper cites TimeRewind: Rewinding Time with Image-and-Events Video Diffusion.

Learning Normal Flow Directly From Event Neighborhoods TimeRewind: Rewinding Time with Image-and-Events Video Diffusion

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.426310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dbc37052-fbeb-45ec-aafa-0a0ffbf7386b · outbound

This paper cites Optical flow es- timation from event-based cameras and spiking neural net- works.

Learning Normal Flow Directly From Event Neighborhoods Optical flow es- timation from event-based cameras and spiking neural net- works

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.792618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 30c2ee58-5921-44ab-9d73-6ff9e9d67b65 · outbound

This paper cites Passive navigation as a pattern recogni- tion problem.

Learning Normal Flow Directly From Event Neighborhoods Passive navigation as a pattern recogni- tion problem

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.785446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a16bffd6-3423-4589-bda7-6667eb4eebe9 · outbound

This paper cites A unifying contrast maximization framework for event cam- eras, with applications to motion, depth, and optical flow estimation.

Learning Normal Flow Directly From Event Neighborhoods A unifying contrast maximization framework for event cam- eras, with applications to motion, depth, and optical flow estimation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.778153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9509b01f-079d-4b62-a11a-951828f0f93f · outbound

This paper cites E-raft: Dense optical flow from event cam- eras.

Learning Normal Flow Directly From Event Neighborhoods E-raft: Dense optical flow from event cam- eras

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.769882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f9510d97-50a7-4f15-99df-aed9e26021db · outbound

This paper cites E-raft: Dense optical flow from event cam- eras.

Learning Normal Flow Directly From Event Neighborhoods E-raft: Dense optical flow from event cam- eras

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.762948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ec341f40-16dc-4d0c-978d-2ce37f5f6ab7 · outbound

This paper cites Dense continuous-time optical flow from event cameras.

Learning Normal Flow Directly From Event Neighborhoods Dense continuous-time optical flow from event cameras

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.756037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 47c06a2d-94dc-4296-9459-4985c4addb62 · outbound

This paper cites Self-supervised learning of event-based optical flow with spiking neural networks.

Learning Normal Flow Directly From Event Neighborhoods Self-supervised learning of event-based optical flow with spiking neural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.747113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fdc9d177-c58b-4661-8a6b-7a7cf57e42cc · outbound

This paper cites Event-Aided Time-to-Collision Estimation for Autonomous Driving.

Learning Normal Flow Directly From Event Neighborhoods Event-Aided Time-to-Collision Estimation for Autonomous Driving

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.415678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a8d6acde-ea27-4656-8868-1c5f44381316 · outbound

This paper cites Blinkflow: A dataset to push the limits of event-based optical flow estimation.

Learning Normal Flow Directly From Event Neighborhoods Blinkflow: A dataset to push the limits of event-based optical flow estimation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.739365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 90c20c9b-a693-40f2-b0fb-5fa766f14b5c · outbound

This paper cites Tma: Temporal motion aggregation for event-based optical flow.

Learning Normal Flow Directly From Event Neighborhoods Tma: Temporal motion aggregation for event-based optical flow

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.731109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9563011f-9fa3-4785-9f73-5ab9454c8637 · outbound

This paper cites Adaptive time-slice block- matching optical flow algorithm for dynamic vision sensors.

Learning Normal Flow Directly From Event Neighborhoods Adaptive time-slice block- matching optical flow algorithm for dynamic vision sensors

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.722431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 76073f0a-2126-4c66-978a-b5a8e9dccd26 · outbound

This paper cites Edflow: Event driven opti- cal flow camera with keypoint detection and adaptive block matching.

Learning Normal Flow Directly From Event Neighborhoods Edflow: Event driven opti- cal flow camera with keypoint detection and adaptive block matching

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.714004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation df318bd9-14b4-4e7d-a26a-765a818791f3 · outbound

This paper cites Event-based Visual Inertial Velometer.

Learning Normal Flow Directly From Event Neighborhoods Event-based Visual Inertial Velometer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.156723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e3a7904-7186-4842-b1fc-d4a5c1439fae · outbound

This paper cites Learning optical flow from event camera with rendered dataset.

Learning Normal Flow Directly From Event Neighborhoods Learning optical flow from event camera with rendered dataset

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.705966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 261273da-bae4-4ce2-b888-adb71df54873 · outbound

This paper cites Efficient meshflow and opti- cal flow estimation from event cameras.

Learning Normal Flow Directly From Event Neighborhoods Efficient meshflow and opti- cal flow estimation from event cameras

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.696764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 49f9ce32-eb2b-4873-984d-25381a88dbcb · outbound

This paper cites Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework.

Learning Normal Flow Directly From Event Neighborhoods Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.165906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8dce70b-e3ea-43c1-8744-0b2612c0df85 · outbound

This paper cites Lifetime estimation of events from dynamic vision sensors.

Learning Normal Flow Directly From Event Neighborhoods Lifetime estimation of events from dynamic vision sensors

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.688053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bc9bdf16-1e21-41d9-9e8a-074af9144e97 · outbound

This paper cites Diffposenet: Di- rect differentiable camera pose estimation.

Learning Normal Flow Directly From Event Neighborhoods Diffposenet: Di- rect differentiable camera pose estimation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.679398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3a617136-4574-4e14-8e11-5699e3a23827 · outbound

This paper cites Taming contrast max- imization for learning sequential, low-latency, event-based optical flow.

Learning Normal Flow Directly From Event Neighborhoods Taming contrast max- imization for learning sequential, low-latency, event-based optical flow

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.670660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation faeb8c0f-8aaf-4c86-8f43-18ea0dc4bbc8 · outbound

This paper cites Vertical landing for micro air vehicles using event-based optical flow.

Learning Normal Flow Directly From Event Neighborhoods Vertical landing for micro air vehicles using event-based optical flow

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.662442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation aeae0475-83df-4eab-9c33-5625abc3d503 · outbound

This paper cites Event-based temporally dense optical flow estimation with sequential learning.

Learning Normal Flow Directly From Event Neighborhoods Event-based temporally dense optical flow estimation with sequential learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.654214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 14a255a8-62e6-416a-a65a-d2703f2a6414 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Learning Normal Flow Directly From Event Neighborhoods Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.184994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08f01142-702b-4d3e-b339-8393b886d706 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space.

Learning Normal Flow Directly From Event Neighborhoods Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.188130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d634d419-b0cf-4a6f-9a15-504fed34e6cd · outbound

This paper cites SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition.

Learning Normal Flow Directly From Event Neighborhoods SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.191123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6678e844-ce8d-4ab8-947d-e697d715ad2e · outbound

This paper cites Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMamba.

Learning Normal Flow Directly From Event Neighborhoods Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMamba

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.194515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98b331b9-0480-4d7d-b593-d76ea8a4eab2 · outbound

This paper cites Motion and Structure from Event-based Normal Flow.

Learning Normal Flow Directly From Event Neighborhoods Motion and Structure from Event-based Normal Flow

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.381691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b072d879-10b3-4c26-9b13-4191ce0ceb0e · outbound

This paper cites Eventnet: Asynchronous recursive event processing.

Learning Normal Flow Directly From Event Neighborhoods Eventnet: Asynchronous recursive event processing

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.636858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 56d89dc1-d807-4e75-a2a9-0b79c08d0053 · outbound

This paper cites Fast event-based optical flow estimation by triplet matching.

Learning Normal Flow Directly From Event Neighborhoods Fast event-based optical flow estimation by triplet matching

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.627348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e44256e3-46ab-43bf-b8d1-aa61a8c1beb5 · outbound

This paper cites Secrets of event-based optical flow.

Learning Normal Flow Directly From Event Neighborhoods Secrets of event-based optical flow

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.618758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6f462787-b230-492a-95f4-5c863b4fe36d · outbound

This paper cites Deep Complex Networks.

Learning Normal Flow Directly From Event Neighborhoods Deep Complex Networks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.211474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2af4c8c2-a2f0-4087-93ad-782fe672c3bf · outbound

This paper cites Learning dense and continuous optical flow from an event camera.

Learning Normal Flow Directly From Event Neighborhoods Learning dense and continuous optical flow from an event camera

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.609514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f8c783c1-6ec2-4079-bca8-4afe30aab232 · outbound

This paper cites Rpeflow: Multimodal fusion of rgb-pointcloud-event for joint optical flow and scene flow estimation.

Learning Normal Flow Directly From Event Neighborhoods Rpeflow: Multimodal fusion of rgb-pointcloud-event for joint optical flow and scene flow estimation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.601148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation db56722e-6c55-4379-bfd6-d9c1f5a9e934 · outbound

This paper cites Event-based optical flow via trans- forming into motion-dependent view.

Learning Normal Flow Directly From Event Neighborhoods Event-based optical flow via trans- forming into motion-dependent view

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.592631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b6e8ea0b-45be-41d8-a4c8-6cd566dcf861 · outbound

This paper cites Space-time event clouds for gesture recognition: From rgb cameras to event cameras.

Learning Normal Flow Directly From Event Neighborhoods Space-time event clouds for gesture recognition: From rgb cameras to event cameras

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.222742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d55c98d6-954d-43b4-8ace-08b83f91e4cf · outbound

This paper cites Mpct: Multiscale point cloud trans- former with a residual network.

Learning Normal Flow Directly From Event Neighborhoods Mpct: Multiscale point cloud trans- former with a residual network

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.578769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 901473d7-af90-43b5-855a-e81d6d8cac3d · outbound

This paper cites Lightweight event-based optical flow estimation via iterative deblurring.

Learning Normal Flow Directly From Event Neighborhoods Lightweight event-based optical flow estimation via iterative deblurring

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.570427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 67a5e6b8-f1de-4db0-a47d-b31c1a82a6c3 · outbound

This paper cites Event3DGS: Event-Based 3D Gaussian Splatting for High-Speed Robot Egomotion.

Learning Normal Flow Directly From Event Neighborhoods Event3DGS: Event-Based 3D Gaussian Splatting for High-Speed Robot Egomotion

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.230926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30b67ec6-cef4-482a-9b27-b7d22ec34f7d · outbound

This paper cites Event-based Optical Flow on Neuromorphic Processor: ANN vs. SNN Comparison based on Activation Sparsification.

Learning Normal Flow Directly From Event Neighborhoods Event-based Optical Flow on Neuromorphic Processor: ANN vs. SNN Comparison based on Activation Sparsification

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.359591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f0a9c13b-c327-4cc0-b5be-98cbb9ae3f67 · outbound

This paper cites Modeling point clouds with self-attention and gumbel subset sampling.

Learning Normal Flow Directly From Event Neighborhoods Modeling point clouds with self-attention and gumbel subset sampling

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.561905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4e0ee1cf-03c6-41b9-88e3-eedbac71ec3b · outbound

This paper cites Towards Anytime Optical Flow Estimation with Event Cameras.

Learning Normal Flow Directly From Event Neighborhoods Towards Anytime Optical Flow Estimation with Event Cameras

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.239764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 472c2bc1-7095-4031-b171-0a3aa59b4590 · outbound

This paper cites Vector-Symbolic Architecture for Event-Based Optical Flow.

Learning Normal Flow Directly From Event Neighborhoods Vector-Symbolic Architecture for Event-Based Optical Flow

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.341590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1290476e-57c1-4624-a8e5-b9b7cd5db270 · outbound

This paper cites Decodable and Sample Invariant Continuous Object Encoder.

Learning Normal Flow Directly From Event Neighborhoods Decodable and Sample Invariant Continuous Object Encoder

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:13:23.330624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f7b967b2-1ac5-476d-8543-7f65e74c1300 · outbound

This paper cites A linear time and space lo- cal point cloud geometry encoder via vectorized kernel mix- ture (VecKM).

Learning Normal Flow Directly From Event Neighborhoods A linear time and space lo- cal point cloud geometry encoder via vectorized kernel mix- ture (VecKM)

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.552630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4088b887-d09e-4377-934c-e36ffc214779 · outbound

This paper cites Cross-modal learning for optical flow estimation with events.

Learning Normal Flow Directly From Event Neighborhoods Cross-modal learning for optical flow estimation with events

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.544728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e8ef57db-9989-4ae0-b178-a312c7c26517 · outbound

This paper cites Starting from non-parametric networks for 3d point cloud analysis.

Learning Normal Flow Directly From Event Neighborhoods Starting from non-parametric networks for 3d point cloud analysis

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.536427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 592d0296-ff2d-483b-8712-545e3648593e · outbound

This paper cites Event-based optical flow estimation with spatio-temporal backpropagation trained spiking neural network.

Learning Normal Flow Directly From Event Neighborhoods Event-based optical flow estimation with spatio-temporal backpropagation trained spiking neural network

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.528425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e9882cb3-e4e0-4995-bd31-ec543c4554e7 · outbound

This paper cites Point transformer.

Learning Normal Flow Directly From Event Neighborhoods Point transformer

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.261797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55b83fc9-5368-4798-804b-f8ae4039e2b1 · outbound

This paper cites Learning optical flow from continu- ous spike streams.

Learning Normal Flow Directly From Event Neighborhoods Learning optical flow from continu- ous spike streams

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.516514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6807e95a-c25a-49a8-8502-fb3a3f3c2ef9 · outbound

This paper cites The multi- vehicle stereo event camera dataset: An event camera dataset for 3d perception.

Learning Normal Flow Directly From Event Neighborhoods The multi- vehicle stereo event camera dataset: An event camera dataset for 3d perception

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.507315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a0a93122-188e-42de-bf8e-32f57e69967e · outbound

This paper cites EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras.

Learning Normal Flow Directly From Event Neighborhoods EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T15:13:23.270582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89d282e2-aa03-4a38-b16b-bad895b93234 · outbound

This paper cites Unsupervised event-based learning of optical flow, depth, and egomotion.

Learning Normal Flow Directly From Event Neighborhoods Unsupervised event-based learning of optical flow, depth, and egomotion

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.499539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2aa9447f-0667-4edc-aaa5-97eb20a00c5f · outbound

This paper cites These visualiza- tions showcase predictions from models trained on each of the three datasets.

Learning Normal Flow Directly From Event Neighborhoods These visualiza- tions showcase predictions from models trained on each of the three datasets

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.491469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 72efb116-16b8-42b2-a04f-949e8ebc4968 · outbound

This paper cites MVSEC & EVIMO2 both provide frame-based forward optical flows in the distorted camera coordinates.

Learning Normal Flow Directly From Event Neighborhoods MVSEC & EVIMO2 both provide frame-based forward optical flows in the distorted camera coordinates

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.483436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bd786f83-976e-40f8-8c5f-af4bddaca4d9 · outbound

This paper cites The resulting flows are then scaled such that their unit is in pixels per second.

Learning Normal Flow Directly From Event Neighborhoods The resulting flows are then scaled such that their unit is in pixels per second

Reference 69

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T15:13:23.475828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f1463c9f-2adb-473e-b0a2-60fd57461032 · outbound

This paper cites The models are trained on EVIMO2-imo training set to better capture the impact of the ablated factors.

Learning Normal Flow Directly From Event Neighborhoods The models are trained on EVIMO2-imo training set to better capture the impact of the ablated factors

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:13:23.466345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ebe7a9d8-cb9e-47e8-b29a-eea95be346ec · outbound

This paper cites an unresolved cited work.

Learning Normal Flow Directly From Event Neighborhoods Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:13:23.458632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9f027222-d304-46a7-b70d-62acb71ddec6 · outbound

This paper cites an unresolved cited work.

Learning Normal Flow Directly From Event Neighborhoods Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:13:23.451044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation b6b3592e-60e1-41fb-add7-7af37094e3d6 · inbound

Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation cites this paper.

Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation Learning Normal Flow Directly From Event Neighborhoods

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T18:35:26.587738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa4bd4da-d0c3-44fa-9150-34733b689435 · inbound

EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects cites this paper.

EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects Learning Normal Flow Directly From Event Neighborhoods

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T10:52:50.006830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7fed3e4-b270-47c9-b82e-9bd5d766a55c · inbound

Motion Segmentation and Egomotion Estimation from Event-Based Normal Flow cites this paper.

Motion Segmentation and Egomotion Estimation from Event-Based Normal Flow Learning Normal Flow Directly From Event Neighborhoods

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T15:59:05.659591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27c0f5f8-ec02-43bd-a473-9f1aacbef3b5 · inbound

LC-Flow: Learning Local Continuous Optical Flow and Confidence from events cites this paper.

LC-Flow: Learning Local Continuous Optical Flow and Confidence from events Learning Normal Flow Directly From Event Neighborhoods

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:14:45.636498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.