Paper Citation Record · LEDGER

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation

As of 13 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2412.08849.

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

pith.paper-citation-record.v1
2412.08849 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:35:29.912659Z

measured 13 of 13 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy9
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e4fd51f-58b6-4bfb-afc7-98b193e9d75d · outbound

This paper cites Haste: multi-hypothesis asynchronous speeded-up tracking of events.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Haste: multi-hypothesis asynchronous speeded-up tracking of events

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:30.071882Z

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 156c5d60-88f5-43b8-bac1-8bc272caf290 · outbound

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

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Lightweight event-based optical flow estimation via iterative deblurring

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:30.020586Z

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 96e29d2f-4c63-4900-82c3-94213c4d105d · outbound

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

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Towards Anytime Optical Flow Estimation with Event Cameras

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T17:35:29.889115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d2323cd-6dcd-4cd3-ac61-13f786677b84 · outbound

This paper cites V2ce: Video to continuous events simulator.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation V2ce: Video to continuous events simulator

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:30.008819Z

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 9889dd38-b5e3-4bbd-b6fd-6b3df9a7e641 · outbound

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

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T17:35:29.897334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36cd64af-5b4c-45e7-907b-f8d4030c702f · outbound

This paper cites Detailed ablation studies focus on different bin configurations for Labits and V oxel Grid, specifically in the context of trajectory estimation.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Detailed ablation studies focus on different bin configurations for Labits and V oxel Grid, specifically in the context of trajectory estimation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:29.985848Z

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 0e2ab972-52a4-4bcf-8244-e7ff662b526e · outbound

This paper cites Further- more, Table 8 details the performance metrics of the complete model pipeline that incorporates the V oxel-to-APLOF features and voxel.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Further- more, Table 8 details the performance metrics of the complete model pipeline that incorporates the V oxel-to-APLOF features and voxel

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:29.974928Z

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 08b7341d-b2ba-4526-9494-5bec3bb98aa1 · outbound

This paper cites This comparison not only facilitates a thorough evaluation of each representation’s efficacy under consistent conditions but also validates the effectiveness of Labits.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation This comparison not only facilitates a thorough evaluation of each representation’s efficacy under consistent conditions but also validates the effectiveness of Labits

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:29.963207Z

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 0f338bfe-4a93-42d1-899c-270061067c32 · outbound

This paper cites U-net: Convolutional networks for biomed- ical image segmentation.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation U-net: Convolutional networks for biomed- ical image segmentation

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T17:35:29.876999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d14aae6-9f64-4f5a-9e99-028c16e5be55 · outbound

This paper cites an unresolved cited work.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:35:29.996360Z

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 7cfe8953-5170-4aa0-9100-9234a188c1cd · outbound

This paper cites Dsec: A stereo event camera dataset for driving scenarios.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Dsec: A stereo event camera dataset for driving scenarios

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:30.061151Z

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 855a78b2-7c72-48ba-9012-22f8bed81709 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Raft: Recurrent all-pairs field transforms for optical flow

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:30.031798Z

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 b8cd40a7-0578-45d2-a076-4d3752006ddf · outbound

This paper cites Adaptive-spikenet: event-based optical flow estimation using spiking neural networks with learnable neuronal dynamics.

Labits: Layered Bidirectional Time Surfaces Representation for Event Camera-based Continuous Dense Trajectory Estimation Adaptive-spikenet: event-based optical flow estimation using spiking neural networks with learnable neuronal dynamics

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:35:30.049382Z

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

No inbound Pith citation observations are available.