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Paper Citation Record · LEDGER

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting

As of 15 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2411.13840.

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

pith.paper-citation-record.v1
2411.13840 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:52:50.365828Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b2777d94-7d45-41c6-a397-a68ba55a411e · outbound

This paper cites Foundational Models Defining a New Era in Vision: A Survey and Outlook.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Foundational Models Defining a New Era in Vision: A Survey and Outlook

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 341276cb-9454-49f5-9ef1-6e10a57b1ec0 · outbound

This paper cites Plenoptic flow: Closed-form visual odom- etry for light field cameras.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Plenoptic flow: Closed-form visual odom- etry for light field cameras

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.818702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 169c4863-f190-4118-8df3-8af9e99610d3 · outbound

This paper cites Zero123-6D: Zero-shot Novel View Synthesis for RGB Category-level 6D Pose Estimation.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Zero123-6D: Zero-shot Novel View Synthesis for RGB Category-level 6D Pose Estimation

Reference 3

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Unavailable: canonical work link unavailable.

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Observation c5ab682f-15dc-465b-ba0e-85d6941b48fe · outbound

This paper cites NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting).

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)

Reference 4

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no resolver link, observed 2026-08-12T15:52:50.252010Z

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Observation b9417cc8-7047-47a5-bdef-855893ee2cc2 · outbound

This paper cites ALFO: Adaptive light field over- segmentation.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting ALFO: Adaptive light field over- segmentation

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.804955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 60b1a22f-c818-4d69-a8ad-758678b48888 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Masked autoencoders are scalable vision learners

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.260181Z digest=sha256:18866ccdbf5b55f0301399aa67072f4644b114a68827f94c010f7073c7fe961c

Observation 8d171ff9-6e68-4e28-9401-39065ac8ef08 · outbound

This paper cites Su- perrays for efficient light field processing.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Su- perrays for efficient light field processing

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.782119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 72a17cfd-f346-40a0-88f9-c874ce299cf1 · outbound

This paper cites On linear structure from motion for light field cameras.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting On linear structure from motion for light field cameras

Reference 8

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raw_fallback, observed 2026-08-12T15:52:50.766897Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 8851b96e-3ede-4117-baae-4b1260488afd · outbound

This paper cites View-consistent 4D Figure 2.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting View-consistent 4D Figure 2

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation eb46b772-c3e1-4ec2-a179-f7ac08d3da71 · outbound

This paper cites Segment Anything.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Segment Anything

Reference 10

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source=pdf_text observed=2026-08-12T15:52:50.275931Z digest=sha256:1a3cb0e33e2de2b1d84ed1e15d9aeb23d3e308cdac1e07b07b06a563ad2885bf

Observation f334411c-a66a-41a0-960a-6acc9d966a51 · outbound

This paper cites Light field rendering.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Light field rendering

Reference 11

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6e2223bb-c1dc-42db-9da7-5639234b8c47 · outbound

This paper cites Neural scene flow prior.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Neural scene flow prior

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ae9b3a7c-6989-4023-b969-adc51b1a08ed · outbound

This paper cites Entropy rate superpixel segmentation.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Entropy rate superpixel segmentation

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4952b60e-85d7-4c4b-b33f-1b1269586631 · outbound

This paper cites 4D light field segmentation from light field super-pixel hyper- graph representation.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting 4D light field segmentation from light field super-pixel hyper- graph representation

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.705495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation a18c38a3-bc2e-4b59-9244-466d1cf5f9d4 · outbound

This paper cites Segment anything in medical images.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Segment anything in medical images

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 058dcc2c-a639-41b5-9b47-10eaf869c7da · outbound

This paper cites 3d scene flow from 4d light field gradients.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting 3d scene flow from 4d light field gradients

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.683474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d48b98f8-5420-49be-97f6-85daa596abda · outbound

This paper cites Deep rigid instance scene flow.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Deep rigid instance scene flow

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:52:50.302526Z digest=sha256:c62e02d6f880213c396d7cd4530efa741781631bef2f418a39e4e36344c35526

Observation 8304462f-bf5c-4412-8683-f1db7885b517 · outbound

This paper cites NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Reference 18

Resolution
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Unavailable: canonical work link unavailable.

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Observation 692a2746-8efd-4e1a-b723-61aee0041340 · outbound

This paper cites Fast depth estimation for light field cam- eras.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Fast depth estimation for light field cam- eras

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 50a09c85-f8ca-4e71-99a4-e18841f49dd1 · outbound

This paper cites Superpixel benchmark and comparison.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Superpixel benchmark and comparison

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9ecef1ef-691d-4031-afaa-e53a5e209a21 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting SAM 2: Segment Anything in Images and Videos

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.318258Z digest=sha256:bafb06f27fb90f0fc2010f2fac2895cd7a80e1617e10c24d6798351b3f5ec8c0

Observation 8e5d16f1-e7bc-40a4-8fdc-a91ac926b10c · outbound

This paper cites Urbanlf: A comprehensive light field dataset for semantic segmentation of urban scenes.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Urbanlf: A comprehensive light field dataset for semantic segmentation of urban scenes

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.622947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6810f4cf-b954-4e33-888c-749a45dbd084 · outbound

This paper cites Oriented light-field windows for scene flow.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Oriented light-field windows for scene flow

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.609768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 651868d5-4f0b-46cf-a454-ed3f2e0cf8ba · outbound

This paper cites Distinguishing refracted features using light field cameras with application to structure from motion.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Distinguishing refracted features using light field cameras with application to structure from motion

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.597514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation bd1bcb80-2202-4f21-b035-1b662b01f765 · outbound

This paper cites Occlusion-aware depth estimation using light-field cameras.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Occlusion-aware depth estimation using light-field cameras

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.584240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:52:50.334653Z digest=sha256:4c3a1eebe36feda1833940b035c335543d506bd5c4212e42260947c741201b49

Observation 5800fc0d-aa2e-43fe-8123-81f4f2b7052a · outbound

This paper cites Variational light field analysis for disparity estimation and super-resolution.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Variational light field analysis for disparity estimation and super-resolution

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.570264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0e91d442-1ca2-4b27-9cb6-e82278558f49 · outbound

This paper cites Foundationpose: Unified 6d pose estimation and tracking of novel objects.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Foundationpose: Unified 6d pose estimation and tracking of novel objects

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.556297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:52:50.341744Z digest=sha256:d719d90578fa12ef064cd40a617ae007b0598c909c46f45736b5aebe84a65e9a

Observation e6782163-ea1b-4812-8e05-b5c1bd16777f · outbound

This paper cites Light field image processing: An overview.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Light field image processing: An overview

Reference 28

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e0481a11-9b3f-4e63-91e0-ad8ae1580921 · outbound

This paper cites PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

Reference 29

Resolution
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no resolver link, observed 2026-08-12T15:52:50.349536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.349536Z digest=sha256:48f0ebdfb2549069f9eb30f5ae32c9810ee167476a12f7c08b3f5fdef5b566f4

Observation d4d22d10-4fee-4952-8c84-1a65a4e63ed5 · outbound

This paper cites Track Anything: Segment Anything Meets Videos.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Track Anything: Segment Anything Meets Videos

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-12T15:52:50.353824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation af1e9d71-ab92-44d6-a0b3-ea8a47fbc37a · outbound

This paper cites From the cal- ibration of a light-field camera to direct plenoptic odome- try.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting From the cal- ibration of a light-field camera to direct plenoptic odome- try

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.535321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 47e46db3-ef61-4ecb-afa6-0ef3bf589783 · outbound

This paper cites 4D light field super- pixel and segmentation.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting 4D light field super- pixel and segmentation

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.520168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:52:50.361830Z digest=sha256:c7810c46af6e7243ef98bf9897e8ef8ad7f23be5dbd6caf97ddf37f5655a0779

Observation 2f80b83b-5ae5-4008-a6f0-332c5e080ca2 · outbound

This paper cites Segment everything everywhere all at once.

Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting Segment everything everywhere all at once

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:52:50.503794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T15:52:50.365828Z digest=sha256:8a3ba52075c381b3e2b16d9e741b8a399aba4642bf9c111de98ae12b636739ec

Pith citing papers

No inbound Pith citation observations are available.