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Paper Citation Record · LEDGER

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2505.07715.

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

pith.paper-citation-record.v1
2505.07715 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

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measured 52 of 52 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

52 of 52 outbound references displayed

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  • verified fuzzy29
  • unresolved22
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77704a7e-5d23-4bde-b1d6-d3ea8d8611ba · outbound

This paper cites write newline.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras write newline

Reference 1

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source=arxiv_source observed=2026-08-15T22:15:03.245996Z digest=sha256:6c204968a9393ee74edb5bc5b05d4625808851ce36b914e37ab261f798da8127

Observation edf8f40e-564e-47c7-a715-11ad520a284c · outbound

This paper cites Toward Transformer-Based Object Detection.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Toward Transformer-Based Object Detection

Reference 2

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Observation 942b4c07-87ee-4fa9-a805-57bae9ce9102 · outbound

This paper cites B., Schwaiger, F., Kreuzberg, L., and Behnke, S.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras B., Schwaiger, F., Kreuzberg, L., and Behnke, S

Reference 3

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Observation 1b5e3bf1-a9fb-4955-aa2c-7ec2024493b1 · outbound

This paper cites A differentiable recurrent surface for asynchronous event-based data.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras A differentiable recurrent surface for asynchronous event-based data

Reference 4

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Observation 7da73d53-af36-4be4-94c0-e3964add94bf · outbound

This paper cites End-to-end object detection with transformers.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras End-to-end object detection with transformers

Reference 5

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Observation a1a1b0cc-1112-46bf-991c-1d4b13ce0701 · outbound

This paper cites Optimised spatio-temporal descriptors for real-time fall detection: comparison of svm and adaboost based classification.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Optimised spatio-temporal descriptors for real-time fall detection: comparison of svm and adaboost based classification

Reference 6

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Observation 683fefb0-fd94-410c-b816-b20d20a7f340 · outbound

This paper cites Object detection with spiking neural networks on automotive event data.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Object detection with spiking neural networks on automotive event data

Reference 7

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Source-reported events for the cited work

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Observation 2f323f78-1312-4d57-bc94-b02ae9c371ad · outbound

This paper cites A Large Scale Event-based Detection Dataset for Automotive.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras A Large Scale Event-based Detection Dataset for Automotive

Reference 8

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Observation 85b7672f-6620-4573-84c1-892227f89296 · outbound

This paper cites Camera-based fall detection on real world data.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Camera-based fall detection on real world data

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation aace6d34-bd55-4218-8663-36d785ac3f55 · outbound

This paper cites Sfod: Spiking fusion object detector.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Sfod: Spiking fusion object detector

Reference 10

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Observation 71cb037f-22e8-4ddb-b7d9-2f9d20572147 · outbound

This paper cites SpikeDet: Better Firing Patterns for Accurate and Energy-Efficient Object Detection with Spiking Neural Networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras SpikeDet: Better Firing Patterns for Accurate and Energy-Efficient Object Detection with Spiking Neural Networks

Reference 11

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Observation 0a5f4448-4a77-4327-99be-bb5c43905634 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras YOLOX: Exceeding YOLO Series in 2021

Reference 12

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Observation 8c21a3fb-77b5-4864-9e7b-00883c40c680 · outbound

This paper cites and Scaramuzza, D.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras and Scaramuzza, D

Reference 13

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Observation 2d42081d-4135-4349-b3bb-726349b06a4b · outbound

This paper cites and Scaramuzza, D.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras and Scaramuzza, D

Reference 14

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Observation 520f31e0-4c38-41f7-984e-fbb57a4cc247 · outbound

This paper cites Joint a-snn: Joint training of artificial and spiking neural networks via self-distillation and weight factorization.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Joint a-snn: Joint training of artificial and spiking neural networks via self-distillation and weight factorization

Reference 15

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.506163Z digest=sha256:8746a7508819a3d5ac87e35267c98cea185792ef69d5aed3a3529ac0b06449b2

Observation 7c4a2fab-0ec3-4294-bfad-ef980fbd6f29 · outbound

This paper cites Spatio-temporal aggregation transformer for object detection with neuromorphic vision sensors.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Spatio-temporal aggregation transformer for object detection with neuromorphic vision sensors

Reference 16

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Observation 29fecd6e-5302-46cd-a2ef-910a8047defa · outbound

This paper cites Lt-snn: Self-adaptive spiking neural network for event-based classification and object detection.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Lt-snn: Self-adaptive spiking neural network for event-based classification and object detection

Reference 17

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Observation 4bceacfd-eaea-40cf-9403-85debd76bf82 · outbound

This paper cites and Schmidhuber, J.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras and Schmidhuber, J

Reference 18

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Observation 11613489-df22-4a79-9b85-0ed9e1657490 · outbound

This paper cites Spiking deep residual networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Spiking deep residual networks

Reference 19

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Observation 0f1d6ec4-5654-450a-8096-bcb803ea08bb · outbound

This paper cites Fast-snn: Fast spiking neural network by converting quantized ann.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Fast-snn: Fast spiking neural network by converting quantized ann

Reference 20

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Observation 06a517d1-a282-4dd1-ae41-fd5725ba16d4 · outbound

This paper cites Towards event-driven object detection with off-the-shelf deep learning.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Towards event-driven object detection with off-the-shelf deep learning

Reference 21

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source=arxiv_source observed=2026-08-15T22:15:03.535108Z digest=sha256:3345925d4fc59d743fba0a86d1cbb59ed0457321ebdd9fdfaba9682ea9faf34e

Observation dc02379d-e62a-44b0-9c16-1fa5e465e166 · outbound

This paper cites and Ba, J.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras and Ba, J

Reference 22

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source=arxiv_source observed=2026-08-15T22:15:03.539633Z digest=sha256:a147e8dc02492fa9fad7f54c02bb4e33754752fc56396ba1997d7ddcdb70b292

Observation 4618def6-28b7-46ac-9090-ceb7519013e1 · outbound

This paper cites Sodformer: Streaming object detection with transformer using events and frames.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Sodformer: Streaming object detection with transformer using events and frames

Reference 23

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Observation ee9c6ee6-6b46-4859-b4d1-2715e04da930 · outbound

This paper cites Asynchronous spatio-temporal memory network for continuous event-based object detection.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Asynchronous spatio-temporal memory network for continuous event-based object detection

Reference 24

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2a454143-0687-4927-ba98-42aeadc46f6d · outbound

This paper cites Graph-based asynchronous event processing for rapid object recognition.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Graph-based asynchronous event processing for rapid object recognition

Reference 25

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source=arxiv_source observed=2026-08-15T22:15:03.555103Z digest=sha256:2d43e2cd4308691213395ab01c2c66a08371b28ea9979e2bbff7713eb2de1596

Observation dd00dc84-3186-4b64-8fb9-24190c8dbd5d · outbound

This paper cites Motion robust high-speed light-weighted object detection with event camera.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Motion robust high-speed light-weighted object detection with event camera

Reference 26

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Observation 331ae763-5d52-460e-b271-bb9b1f2983ab · outbound

This paper cites Short-term traffic flow prediction with conv-lstm.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Short-term traffic flow prediction with conv-lstm

Reference 27

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Source-reported events for the cited work

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Observation 2547a9f8-6da9-4e9a-b820-35ad32017546 · outbound

This paper cites Optical flow-guided 6dof object pose tracking with an event camera.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Optical flow-guided 6dof object pose tracking with an event camera

Reference 28

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Observation 600c5d60-43ae-4c64-b187-f5c03b67d657 · outbound

This paper cites Line-based 6-dof object pose estimation and tracking with an event camera.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Line-based 6-dof object pose estimation and tracking with an event camera

Reference 29

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Observation 398aae50-0f45-4506-b662-1261ef57247a · outbound

This paper cites Stereo event-based, 6-dof pose tracking for uncooperative spacecraft.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Stereo event-based, 6-dof pose tracking for uncooperative spacecraft

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.576614Z digest=sha256:e1f7a31abd752a137a8cb1bfc299f9c7cbf59e6dc14d1d5ab295dcb0aacc24c7

Observation 89ad6a18-15ac-4636-b36a-29585778fe22 · outbound

This paper cites Darwin3: a large-scale neuromorphic chip with a novel isa and on-chip learning.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Darwin3: a large-scale neuromorphic chip with a novel isa and on-chip learning

Reference 31

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source=arxiv_source observed=2026-08-15T22:15:03.580615Z digest=sha256:98dbc6cfff4cb7194f9eafac51c1a5759ffa74d49a5012309076fc3ded207ab2

Observation 45659c5d-6e1a-4f0f-802d-ada388fa895c · outbound

This paper cites Event-based asynchronous sparse convolutional networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Event-based asynchronous sparse convolutional networks

Reference 32

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raw_fallback, observed 2026-08-15T22:15:04.155852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.584621Z digest=sha256:453372fe25d6c690bc744a5347540ca51232eadb2c1558bb03651db6b62b9c8c

Observation ffac44f7-f738-445e-a1a2-91d4926d22a1 · outbound

This paper cites Mixed Precision Training.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Mixed Precision Training

Reference 33

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source=arxiv_source observed=2026-08-15T22:15:03.588158Z digest=sha256:c2dcadfabd40f0498ea866bd7b7b0087be6a0cde22dd1ad4ffa851a92f95796e

Observation f3d0ea0e-9941-4618-b097-f69c1c5bdeca · outbound

This paper cites Get: group event transformer for event-based vision.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Get: group event transformer for event-based vision

Reference 34

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raw_fallback, observed 2026-08-15T22:15:04.143089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.591865Z digest=sha256:0171070f7227a617b8942b67af3f961cd13122425ec5b93ed283d0da4c5f446e

Observation b7e66c43-314f-4dce-9694-8ae736adc55f · outbound

This paper cites Learning to detect objects with a 1 megapixel event camera.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Learning to detect objects with a 1 megapixel event camera

Reference 35

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raw_fallback, observed 2026-08-15T22:15:04.128689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.595111Z digest=sha256:65ac921f431bf8cc41bd0010af607fbb153a0c9cf386656cb1f8810039b46907

Observation bbff1194-83da-4ad7-9e8e-6c6310d40552 · outbound

This paper cites A biomimetic frame-free event-driven image sensor.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras A biomimetic frame-free event-driven image sensor

Reference 36

Resolution
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raw_fallback, observed 2026-08-15T22:15:04.116290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.712223Z digest=sha256:6175ef7ff15e05dfbb5500e18de40f3d3289e7965f04e8e4569ac718d2b2f08e

Observation 40eb3a0d-63f9-4694-883d-e652c53db593 · outbound

This paper cites ESIM : an open event camera simulator.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras ESIM : an open event camera simulator

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:04.104259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.717303Z digest=sha256:59bd16e0935c95ce519808c832cff1804b7799635f3ad923ed4908a639f610cb

Observation e997757d-a4ac-418f-905b-ebda27df1c22 · outbound

This paper cites Aegnn: Asynchronous event-based graph neural networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Aegnn: Asynchronous event-based graph neural networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:04.091829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.720712Z digest=sha256:5e51239ba233f59e11401f51d63b8846737f51805a822cdc68d2e441cafeb440

Observation cc06998e-9227-4546-bc6c-8e111d237593 · outbound

This paper cites and Linares-Barranco, B.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras and Linares-Barranco, B

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:04.076571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.724492Z digest=sha256:a0aa74f63f6c96bb91c195d9049508ebe4d6097fbcab6565f2146dcdc68c77be

Observation 00ad73ff-5938-482c-bf90-2573651ae2f7 · outbound

This paper cites Efficient spiking neural networks with sparse selective activation for continual learning.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Efficient spiking neural networks with sparse selective activation for continual learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.727887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.727887Z digest=sha256:7600d657feee19d9cb7bd7312e86a449772fa067ff2e3aabaaf708a52e63ffd7

Observation 6894cf20-2c1b-4965-8e55-9ab65eeefb4d · outbound

This paper cites Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.731190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.731190Z digest=sha256:05b0a2d209474867ed963e1e95fb42e634cf5734334267528be7c5c9e7c237cf

Observation 0b4c6646-e48e-4c5a-abae-e4d732305e01 · outbound

This paper cites an unresolved cited work.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Unresolved cited work

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.735302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.735302Z digest=sha256:e76b15e4bfc9749f2a084070420d200b47ed3416199a42dcf18aaa3768ecfdce

Observation 8cb4abde-bb6d-4a8d-92ad-81176c1659a4 · outbound

This paper cites Deep directly-trained spiking neural networks for object detection.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Deep directly-trained spiking neural networks for object detection

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:04.055600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.739619Z digest=sha256:8318ebecd556afe3a66d2dc4fe60f0702377bf1dbbfc28b896193378926beb24

Observation d030c946-7b56-42e5-9f73-25bba3833358 · outbound

This paper cites Maxvit: Multi-axis vision transformer.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Maxvit: Multi-axis vision transformer

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:04.043389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.744685Z digest=sha256:6cfc8602090a00a906ac92bbfd6f6b703170f588b53300a73d7114d8121ba19b

Observation 1b36e933-0ec2-4558-bba0-5de8efd673c5 · outbound

This paper cites Eas-snn: End-to-end adaptive sampling and representation for event-based detection with recurrent spiking neural networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Eas-snn: End-to-end adaptive sampling and representation for event-based detection with recurrent spiking neural networks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:04.030037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.748828Z digest=sha256:70879013741e937e464aa281b5d7fcab777d4afa6817f57f5dec6c03b5e52c33

Observation ce18ea32-b847-4b93-b189-ecce8d8f2103 · outbound

This paper cites Enhancing adaptive history reserving by spiking convolutional block attention module in recurrent neural networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Enhancing adaptive history reserving by spiking convolutional block attention module in recurrent neural networks

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.753011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.753011Z digest=sha256:bcb75f847b4346c45e74e77750e54a0f06314211fbb1435883f125f53ebc441a

Observation f9d66a4b-e7e3-47a6-ab50-abd711d8512d · outbound

This paper cites Reversing structural pattern learning with biologically inspired knowledge distillation for spiking neural networks.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Reversing structural pattern learning with biologically inspired knowledge distillation for spiking neural networks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.758923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.758923Z digest=sha256:cc7701aac8da3edd3ab52aa845156ab92d1cd6fe7809218c8780db5b54a3035a

Observation fe53c08a-c24a-4bc9-b4d4-e6fd2bf33d9c · outbound

This paper cites K., Pan, G., and Zhang, Q.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras K., Pan, G., and Zhang, Q

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.763135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.763135Z digest=sha256:494a46da477de83d375d8575512cfc387e772f10a34dd34aedfd1d85b2135d8f

Observation d98990da-2f31-4fc0-8b5d-b5ad259e9acc · outbound

This paper cites Spikingvit: A multiscale spiking vision transformer model for event-based object detection.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Spikingvit: A multiscale spiking vision transformer model for event-based object detection

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.767433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.767433Z digest=sha256:716450e6609d82aaab215d2ade0b6ad4790443295f56aed4a8976ad5122a31ce

Observation 05ea56d7-8f7f-41e3-b266-bd79f9684596 · outbound

This paper cites Automotive object detection via learning sparse events by spiking neurons.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Automotive object detection via learning sparse events by spiking neurons

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:03.991729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.771316Z digest=sha256:9a62fb3df45d62f64810505669fc3e90370c7a6cc9bae110bc0c3f2723da2f79

Observation 4a604cda-2e9f-416f-91fd-9ff01d200b97 · outbound

This paper cites Spikformer: When Spiking Neural Network Meets Transformer.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras Spikformer: When Spiking Neural Network Meets Transformer

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T22:15:03.774984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:15:03.774984Z digest=sha256:8f1e1886c368942bf3f6bc3c7d395557a53482cd3256f9c1fdfbc7f8225584da

Observation f0793394-53af-4752-ad95-33ee7e41ec83 · outbound

This paper cites From chaos comes order: Ordering event representations for object recognition and detection.

Hybrid Spiking Vision Transformer for Object Detection with Event Cameras From chaos comes order: Ordering event representations for object recognition and detection

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:15:03.978799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:15:03.779626Z digest=sha256:d0aedacad4531c0e76b7c1c3475685388369da9b29c18a3f2d9e9a723bce511c

Pith citing papers

No inbound Pith citation observations are available.