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Paper Citation Record · LEDGER

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

As of 22 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 2026-08-21T06:32:19.484+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.

source=pdf_text observed=2026-08-12T15:52:50.238868Z digest=sha256:498b3d68ac0593e4c20c4d1e859c162f63ba7cd89d507af469c88f98baa304ab

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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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 2026-08-21T06:32:19.484+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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.247833Z digest=sha256:631225297ff4e1a2886e65861ff84b6076416afe317e3d5fb6c80c9041b5dbf9

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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source=pdf_text observed=2026-08-12T15:52:50.252010Z digest=sha256:603ce3560dec1d23a4b2b541c8c59f830af3061c5aedba7784d1d8df73882f3f

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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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 2026-08-21T06:32:19.484+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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.260181Z digest=sha256:3c60bbb1e5693c6bf2baccb520c033998ec99d3bc9998546be0233ff46924ae6

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.264104Z digest=sha256:1cbcf2e6ba23ef45627c511d61fa24dd83c092294e232bbfd318f78cf3f0eb22

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 2026-08-21T06:32:19.484+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 2026-08-21T06:32:19.484+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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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.279918Z digest=sha256:871db23afc96dbb645b2ce85826c64d970877ef9d3a75e374e4f337edae00634

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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raw_fallback, observed 2026-08-12T15:52:50.729511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.283571Z digest=sha256:bd04524e4372c5ad8d277b026763c5d3f03718d81386cded54fc71661edf9e61

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.287409Z digest=sha256:3268394dc88cad622ee0255d0f5e499362db150219670a833563d7bf49d57a56

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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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 2026-08-21T06:32:19.484+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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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.298738Z digest=sha256:4c7f39b0a85394fe086fa41ba9c66971335f125c8801d97b69e30ad17df4a306

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.302526Z digest=sha256:76fb2741f68f6c26f6a21a9a8b9b9cd2da641769c7168e4fd4c85594947f8b14

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

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source=pdf_text observed=2026-08-12T15:52:50.306133Z digest=sha256:c76bc7e366756afbe6fdb65d2320f26789d2ef1bb677cffb4be124fd603157bb

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.310447Z digest=sha256:2f9f2b4ba67bea9edff1728b960ac1e5f515f8244c44cc0164b39b6126ad6759

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.314074Z digest=sha256:a0688ae73b72f5b43c4b41715ff9e45a3189ea05d6ea6380f643e2bf2931e57a

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.318258Z digest=sha256:03e2a2fa3e4794a07f30c5cfe708809a77b2fa1b61717876255df2336f848b98

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.322811Z digest=sha256:959b99091696d4e32fa1df394fb6ab68f11a73fe76a3b6314119584844f74d84

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
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+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 2026-08-21T06:32:19.484+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
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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.334653Z digest=sha256:720f611940cf4853a4c365ab267ec493a0157bf2652fab7ac49a59515ad705f4

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

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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 2026-08-21T06:32:19.484+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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.341744Z digest=sha256:1d97d31d907b8d80d3d74756154b82edfcc83b8cb15330c8b8004912e9790f5d

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
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.345502Z digest=sha256:f93a7f49ef492976bf5f85e47fde26c1807525bc370c135241cce1fc8d47b8be

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

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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=sha256:540b346524db0659b3606e9f1294205148f10f278cdf4f4e151f2acd42a0391f

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:52:50.353824Z digest=sha256:37cc08a143c84ce40e872185e0b3717a812a283f2902a92b62dbb0928e996115

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.358233Z digest=sha256:02a67b40d5ee96c693ea3cc2d46a8820e7b312692e6410c56c4f78d30de36337

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.361830Z digest=sha256:717008fc57f44f9ec32039a7a442f3d617a181f1dd2323bcdd9fa75c6ca69eee

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-12T15:52:50.365828Z digest=sha256:758e132210f7f55fa0ddf715d9bd12c0091bbc50695f3c6f91c17dba6f5b3d66

Pith citing papers

No inbound Pith citation observations are available.