EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks | Paper Citation Record

Observation dda9df96-3cc4-4b5c-b05c-ffd0a0069741 · outbound

This paper cites Scaling Egocentric Vision: The EPIC-KITCHENS Dataset.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Scaling Egocentric Vision: The EPIC-KITCHENS Dataset

Reference 1

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Observation 9944baa9-e7ae-41de-bb32-e74ebe22e891 · outbound

This paper cites Online human action detection and anticipation in videos: A survey,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Online human action detection and anticipation in videos: A survey,

Reference 2

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Observation 845a5f07-7aa5-4911-a0da-309e2b282ef8 · outbound

This paper cites Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs

Reference 3

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Observation ba96d034-2b79-41b7-b3d5-9b85a4a9d775 · outbound

This paper cites Event-based Vision for Early Prediction of Manipulation Actions.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Event-based Vision for Early Prediction of Manipulation Actions

Reference 4

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Observation 3bab9a4c-bf9a-4780-a176-d2e411b79c94 · outbound

This paper cites An overview of Human Action Recognition in sports based on Computer Vision,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks An overview of Human Action Recognition in sports based on Computer Vision,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:25.759995Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7074b30d-94c8-43c4-8ce6-db1865f28561 · outbound

This paper cites IMU-based Human Activity Recognition using Machine Learning and Deep Learning models,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks IMU-based Human Activity Recognition using Machine Learning and Deep Learning models,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:25.525698Z

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Observation c367bfcb-b176-4b60-b28a-c9ad095d2175 · outbound

This paper cites Lightweight Deep Learning Model in Mobile-Edge Computing for Radar-Based Human Activity Recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Lightweight Deep Learning Model in Mobile-Edge Computing for Radar-Based Human Activity Recognition,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:25.231893Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a19acc18-3094-459e-a417-93eab3542682 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 8

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Observation fba67fe6-ef03-40b7-b6a7-5c4d71bbd018 · outbound

This paper cites A Survey on Deep Learning Techniques for Action Anticipation.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks A Survey on Deep Learning Techniques for Action Anticipation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:15.500780Z

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Observation b6180b59-e86d-4c8c-b373-5b920a80ef22 · outbound

This paper cites Streaming egocentric action anticipa- tion: An evaluation scheme and approach,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Streaming egocentric action anticipa- tion: An evaluation scheme and approach,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:24.986087Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 82ea993f-8632-4a40-9160-d057b1fac441 · outbound

This paper cites Event-Based Vision: A Survey,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Event-Based Vision: A Survey,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:24.660344Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a3c5abe6-ffbe-47a0-93ee-17829f3e10e4 · outbound

This paper cites Action Recognition and Benchmark Using Event Cam- eras,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Action Recognition and Benchmark Using Event Cam- eras,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:24.374701Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4c0b94a2-4357-4379-8b92-502e36d70f41 · outbound

This paper cites Temporal Binary Representation for Event-Based Action Recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Temporal Binary Representation for Event-Based Action Recognition,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:24.216268Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 585645f2-0dd0-4928-a91d-d185588f5b05 · outbound

This paper cites Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:24.053334Z

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Observation a94aaf34-e739-43e3-9690-fec3afa787cb · outbound

This paper cites Networks of spiking neurons: The third generation of neural network models,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Networks of spiking neurons: The third generation of neural network models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.917723Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61309c0d-1132-4224-b231-afb629fe6b61 · outbound

This paper cites Efficient Neuromorphic Signal Processing with Loihi 2,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Efficient Neuromorphic Signal Processing with Loihi 2,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.770928Z

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Observation 9465716f-3e0d-48a5-bcc9-aa66a8979eb8 · outbound

This paper cites HMDB: A large video database for human motion recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks HMDB: A large video database for human motion recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.620635Z

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Observation 5cd394d3-6172-41e4-9d50-090cd0262ddd · outbound

This paper cites Long-Term Recurrent Convolutional Networks for Visual Recognition and Description,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Long-Term Recurrent Convolutional Networks for Visual Recognition and Description,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.502155Z

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Observation abe82106-dfd8-442f-9d0f-0ea3d0ace1ea · outbound

This paper cites Learning Spatiotemporal Features with 3D Convolutional Networks,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Learning Spatiotemporal Features with 3D Convolutional Networks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.367276Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 053a3910-5189-4c66-8dfe-bdb03d5dd3fd · outbound

This paper cites Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.258097Z

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Observation 99546ef4-283f-4875-9225-96e5ba850da8 · outbound

This paper cites Two-Stream Convolutional Networks for Action Recognition in Videos.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Two-Stream Convolutional Networks for Action Recognition in Videos

Reference 21

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Observation f2db02ec-7aaa-4771-b5f2-1e88e24bb58e · outbound

This paper cites Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:23.093608Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5a06441-ab1f-4402-8ee3-858d146cc9dd · outbound

This paper cites SlowFast Networks for Video Recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks SlowFast Networks for Video Recognition,

Reference 23

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Observation bdafe435-3711-4798-b93f-e3fa8b1b8de7 · outbound

This paper cites Enhancing Video Transformers for Action Understanding with VLM-aided Training.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Enhancing Video Transformers for Action Understanding with VLM-aided Training

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:16.667628Z

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Observation e5519a07-91a7-46c7-b5d9-0a5defe7dc72 · outbound

This paper cites MANTA: Diffusion Mamba for Efficient and Effective Stochastic Long-Term Dense Anticipation.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks MANTA: Diffusion Mamba for Efficient and Effective Stochastic Long-Term Dense Anticipation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:16.751632Z

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Observation 7fa22a40-1d99-494c-8afb-be392f2024c1 · outbound

This paper cites Early event detection based on dynamic images of surveillance videos,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Early event detection based on dynamic images of surveillance videos,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:22.729646Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3d5a9246-6b86-4ae2-b5f1-b531795f3587 · outbound

This paper cites A Low Power, Fully Event-Based Gesture Recognition System,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks A Low Power, Fully Event-Based Gesture Recognition System,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:22.512586Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a97eae4-6810-424b-80f2-523904b1e16a · outbound

This paper cites Neuromorphic Vision Datasets for Pedestrian Detection, Action Recognition, and Fall Detection,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Neuromorphic Vision Datasets for Pedestrian Detection, Action Recognition, and Fall Detection,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:22.365880Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 18da9220-b696-40c0-be29-9363bdbbc2d4 · outbound

This paper cites Event-based Action Recognition Using Motion Information and Spiking Neural Networks,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Event-based Action Recognition Using Motion Information and Spiking Neural Networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:22.167837Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e040f444-2ea7-4957-be65-270cd9aea9ae · outbound

This paper cites Graph-Based Spatio-Temporal Feature Learning for Neu- romorphic Vision Sensing,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Graph-Based Spatio-Temporal Feature Learning for Neu- romorphic Vision Sensing,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:21.970499Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 358be665-0208-48a5-9c18-53c4fc4d9881 · outbound

This paper cites Eventtransact: A video transformer-based framework for event-camera based action recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Eventtransact: A video transformer-based framework for event-camera based action recognition,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:21.829717Z

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Observation 76a293e9-149c-4930-9034-45989e7403b7 · outbound

This paper cites Space-Time Event Clouds for Gesture Recognition: From RGB Cameras to Event Cameras,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Space-Time Event Clouds for Gesture Recognition: From RGB Cameras to Event Cameras,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:21.671590Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 38b726f2-2cd5-4112-8722-105f3ab48836 · outbound

This paper cites Training Spiking Neural Networks Using Lessons From Deep Learning,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Training Spiking Neural Networks Using Lessons From Deep Learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:21.352917Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a2ecafa4-c76f-4595-8f5a-47ec2b1b14cf · outbound

This paper cites Spiking Neural Networks for event-based action recognition: A new task to understand their advantage,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Spiking Neural Networks for event-based action recognition: A new task to understand their advantage,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:21.092690Z

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Observation db5a671f-72a6-445a-b079-667f755f7f9b · outbound

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

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:17.643295Z

Source-reported events for the cited work

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Observation 7db1b5c1-bc39-41b7-a58a-cfa7ae6b5812 · outbound

This paper cites Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition

Reference 36

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Source-reported events for the cited work

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Observation 5d4b271f-851c-4b16-a558-57fff3342b1a · outbound

This paper cites Spike-HAR++: an energy-efficient and lightweight parallel spiking transformer for event-based human action recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Spike-HAR++: an energy-efficient and lightweight parallel spiking transformer for event-based human action recognition,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:20.885481Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation aae4bd53-8cf6-4637-8a42-7801ee714153 · outbound

This paper cites Two-Stream Spiking Neural Network for Event-based Action Recognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Two-Stream Spiking Neural Network for Event-based Action Recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:20.723954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 074d7bf0-289e-4795-b9b4-65cb8e3d0949 · outbound

This paper cites Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:20.563515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bc56c685-1d90-49d8-b352-48afc05d0cb6 · outbound

This paper cites Neuronal Dy- namics: From Single Neurons To Networks And Models Of Cognition,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Neuronal Dy- namics: From Single Neurons To Networks And Models Of Cognition,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:20.415094Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a2748d2d-7849-48cc-8cba-4f4e38a45fd3 · outbound

This paper cites Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation

Reference 41

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Observation ed8e93a9-17fd-4a2b-a4c3-74108910951d · outbound

This paper cites Neuromorphic Lip-Reading with Signed Spiking Gated Recurrent Units,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Neuromorphic Lip-Reading with Signed Spiking Gated Recurrent Units,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:20.310774Z

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Observation 2383e970-80c5-4dde-b56d-b481b5d7b017 · outbound

This paper cites Efficient recurrent architectures through activity sparsity and sparse back-propagation through time.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Efficient recurrent architectures through activity sparsity and sparse back-propagation through time

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:18.427735Z

Source-reported events for the cited work

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Observation c5f17a4b-be4a-4fd6-876f-1e7ccf64c790 · outbound

This paper cites Temporal Contrastive Learning for Spiking Neural Networks.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Temporal Contrastive Learning for Spiking Neural Networks

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:38:19.508574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 500172d7-16ad-4ecb-8aef-ccc64aca666f · outbound

This paper cites ED-sKWS: Early-Decision Spiking Neural Networks for Rapid,and Energy-Efficient Keyword Spotting.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks ED-sKWS: Early-Decision Spiking Neural Networks for Rapid,and Energy-Efficient Keyword Spotting

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:38:19.313348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 85b0dc49-9c3a-440a-81a2-933b70e6cbc0 · outbound

This paper cites NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:38:19.129025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 394a7deb-abb7-4173-8bea-d15f28ea5d22 · outbound

This paper cites Separate visual pathways for perception and action,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Separate visual pathways for perception and action,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:20.156232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9a823a39-1a77-4584-a4eb-64e8474d2a7d · outbound

This paper cites Were RNNs All We Needed?.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Were RNNs All We Needed?

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:18.816732Z

Source-reported events for the cited work

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Observation 0170deb2-23a4-4b2b-8cb7-968774d35bc4 · outbound

This paper cites Comprehensive Survey on Human Motion Tracking System,.

EEvAct: Early Event-Based Action Recognition with High-Rate Two-Stream Spiking Neural Networks Comprehensive Survey on Human Motion Tracking System,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:38:19.990180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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