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Paper Citation Record · LEDGER

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens

As of 10 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 0 inbound Pith citation observations for arXiv:2508.04928.

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

pith.paper-citation-record.v1
2508.04928 v5

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:45:28.041206Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

89 of 89 outbound references displayed

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External citation measurements

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Outbound references

Observation 763eaf14-55a9-4ba5-9fc2-c60408f2a964 · outbound

This paper cites Rotinvmtl: Rotation invariant multinet on fisheye images for autonomous driving applications.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Rotinvmtl: Rotation invariant multinet on fisheye images for autonomous driving applications

Reference 1

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Observation 9acec82e-3607-4394-aa44-3adde7d9e384 · outbound

This paper cites Adabins: Depth estimation using adaptive bins.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Adabins: Depth estimation using adaptive bins

Reference 2

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Observation 1fd29de7-6b26-48e5-b561-aabb1c37a0c3 · outbound

This paper cites Depth pro: Sharp monocular metric depth in less than a second.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depth pro: Sharp monocular metric depth in less than a second

Reference 3

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Observation 71319e7c-0516-4a6c-884e-609e1aec050b · outbound

This paper cites Memory Transformer.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Memory Transformer

Reference 4

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Observation 0d111466-622b-4fd6-aafa-00484630fcda · outbound

This paper cites Transformer-based monocular depth estimation with attention supervision.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Transformer-based monocular depth estimation with attention supervision

Reference 5

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Observation 873b7559-c18d-4755-8d49-a93f7fdf5aa4 · outbound

This paper cites UnCLe: Benchmarking Unsupervised Continual Learning for Depth Completion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens UnCLe: Benchmarking Unsupervised Continual Learning for Depth Completion

Reference 6

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Observation 11db2435-e611-450d-8185-9f41e5f0853e · outbound

This paper cites Adaptive confidence thresholding for monocular depth esti- mation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Adaptive confidence thresholding for monocular depth esti- mation

Reference 7

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Observation e67d1c88-9f34-45f8-b4f8-b609f664cdff · outbound

This paper cites Duncan, and Alex Wong.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Duncan, and Alex Wong

Reference 8

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Observation f955ddfa-4322-49b3-a993-a3839f25994d · outbound

This paper cites Vision Transformers Need Registers.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Vision Transformers Need Registers

Reference 9

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Observation 3f4dd616-9c66-4b96-8ccc-e27c688f485d · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 10

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Observation 5d3d3776-83b9-44fb-bc63-0eb34a8bf4c7 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens An image is worth 16x16 words: Transformers for image recognition at scale

Reference 11

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Observation b49796e3-08f1-4ac7-a096-ad1dabb60e3a · outbound

This paper cites Close-range camera calibration.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Close-range camera calibration

Reference 12

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Observation 650bf0a8-06a0-47c3-ac4f-8e08f34874af · outbound

This paper cites Predicting depth, surface nor- mals and semantic labels with a common multi-scale con- volutional architecture.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Predicting depth, surface nor- mals and semantic labels with a common multi-scale con- volutional architecture

Reference 13

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Observation 1698a1e1-1b02-4151-8bfb-8fb1e648e5b0 · outbound

This paper cites Depth map prediction from a single image using a multi-scale deep net- work.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depth map prediction from a single image using a multi-scale deep net- work

Reference 14

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Observation c93a7610-365e-4ab0-8cf7-22f0181dde85 · outbound

This paper cites All-day depth completion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens All-day depth completion

Reference 15

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Observation 32be1397-8538-4ba6-920c-211215456dd8 · outbound

This paper cites Geo- supervised visual depth prediction.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Geo- supervised visual depth prediction

Reference 16

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Observation 1fb4c0a8-7fe0-47fc-a4a0-164db6c70f4b · outbound

This paper cites Simfir: A simple framework for fisheye image rectification with self-supervised representation learn- ing.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Simfir: A simple framework for fisheye image rectification with self-supervised representation learn- ing

Reference 17

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Observation 3b5dbe8e-ccc6-438f-9cd9-e3d6295dcae4 · outbound

This paper cites Deep ordinal regression net- work for monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Deep ordinal regression net- work for monocular depth estimation

Reference 18

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Observation fdcdbbe6-b3c4-4e9d-ad81-55c5ed911ab2 · outbound

This paper cites Unsupervised cnn for single view depth estimation: Geom- etry to the rescue.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Unsupervised cnn for single view depth estimation: Geom- etry to the rescue

Reference 19

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Observation 02422e19-9092-487c-9092-169cefe79ef8 · outbound

This paper cites Unsupervised monocular depth estimation with left- right consistency.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Unsupervised monocular depth estimation with left- right consistency

Reference 20

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Observation 10754701-76b3-45a4-9b55-f96a8c09fef9 · outbound

This paper cites Digging into self-supervised monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Digging into self-supervised monocular depth estimation

Reference 21

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Observation 178fba5e-e6d1-46d5-89d8-463ee5866f3a · outbound

This paper cites Semantically-guided representation learning for self-supervised monocular depth.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Semantically-guided representation learning for self-supervised monocular depth

Reference 22

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Observation 47d12ff4-a948-4e30-8f53-debd0d3fa659 · outbound

This paper cites 3d packing for self-supervised monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens 3d packing for self-supervised monocular depth estimation

Reference 23

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Observation dbd0d528-e231-44f3-8eeb-4235f2fb2c9a · outbound

This paper cites Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera

Reference 24

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Observation d8f6d7c8-92a9-47fe-8ece-af504e35d952 · outbound

This paper cites Harris and M.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Harris and M

Reference 25

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Observation aa4b6486-5cf7-4081-aa7d-b13f87280b40 · outbound

This paper cites A generic camera calibration method for fish-eye lenses.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens A generic camera calibration method for fish-eye lenses

Reference 26

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Observation 6deddc5b-3462-4192-b962-0ac3141b8fd5 · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 27

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Observation aacc10dd-ea2d-4e80-a3ea-80acab588dad · outbound

This paper cites A history of the photographic lens.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens A history of the photographic lens

Reference 28

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Observation 5d76457c-f79b-45b5-a2d5-c4d0427cab04 · outbound

This paper cites Syndistnet: Self-supervised monocular fisheye camera distance estima- tion synergized with semantic segmentation for autonomous driving.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Syndistnet: Self-supervised monocular fisheye camera distance estima- tion synergized with semantic segmentation for autonomous driving

Reference 29

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Observation bcc21540-3464-445b-a46a-375553e464ee · outbound

This paper cites Deeper depth prediction with fully convolutional residual networks.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Deeper depth prediction with fully convolutional residual networks

Reference 30

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Observation 1b95e121-bfc5-440c-823c-9cff7ef24441 · outbound

This paper cites Sub-token vit embedding via stochastic reso- nance transformers.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Sub-token vit embedding via stochastic reso- nance transformers

Reference 31

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Observation 77caf5fe-9536-47ca-bfd6-1eead50d1704 · outbound

This paper cites On the viabil- ity of monocular depth pre-training for semantic segmenta- tion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens On the viabil- ity of monocular depth pre-training for semantic segmenta- tion

Reference 32

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Source-reported events for the cited work

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Observation 8695d47f-aab8-4f51-8754-f4db59b53781 · outbound

This paper cites Depth and surface normal estimation from monocular images using regression on deep features and hi- erarchical crfs.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depth and surface normal estimation from monocular images using regression on deep features and hi- erarchical crfs

Reference 33

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Source-reported events for the cited work

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Observation 3196c696-ab99-45fb-8cea-ff62fe974620 · outbound

This paper cites Depthformer: Exploiting long-range correlation and local in- formation for accurate monocular depth estimation.Machine Intelligence Research, 20(6):837–854, 2023.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depthformer: Exploiting long-range correlation and local in- formation for accurate monocular depth estimation.Machine Intelligence Research, 20(6):837–854, 2023

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:45:27.807206Z digest=sha256:ed8aee990323610f39a480dac8626dd765dca4f1670fc9a456d53a36695b75f2

Observation f36e4ce9-d5f2-4399-893a-f872797bb14a · outbound

This paper cites Dr-gan: Automatic radial distortion rectification using con- ditional gan in real-time.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Dr-gan: Automatic radial distortion rectification using con- ditional gan in real-time

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.098772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.811556Z digest=sha256:542194869424949429b7078873374e50e7fb11f83f51ddc5420f04f39b6c2a38

Observation 7c699065-3308-4da4-b774-f53ae5edf925 · outbound

This paper cites Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.081569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.816039Z digest=sha256:c138a724f74989d39a2f3b729d766b19b00d14dfe44bc811dfa1c7b0c9f6801a

Observation 63842b32-8f11-45f3-acea-04e48c989555 · outbound

This paper cites Fova-depth: Field-of-view agnostic depth es- timation for cross-dataset generalization.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Fova-depth: Field-of-view agnostic depth es- timation for cross-dataset generalization

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.066183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.820424Z digest=sha256:5c2370793af611ed668c59c8262991618497689c330c61c25db584a21c3f36e3

Observation 43f8b69b-5342-4a8a-b99e-d05f0b8226ad · outbound

This paper cites Learning depth from single monocular images using deep convolutional neural fields.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Learning depth from single monocular images using deep convolutional neural fields

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.051174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.824974Z digest=sha256:613022931d57d532f0d1e1b620a3ab096f600efbfb5117a86f7f8db18b2d5218

Observation b98c151e-ea9c-430b-b43f-3c08866f8dd5 · outbound

This paper cites Monitored distillation for positive congruent depth completion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Monitored distillation for positive congruent depth completion

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.035660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.829387Z digest=sha256:d308acf89e99152675f9eaab27c291367c2f33e9c55d3111ce7b8059957d8c58

Observation bccce437-3dca-43fc-b677-9ebf00b547cc · outbound

This paper cites Hr-depth: High resolution self-supervised monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Hr-depth: High resolution self-supervised monocular depth estimation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.018598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.834240Z digest=sha256:1efb48f560fead69d4a7f50cd5c103602de68e64e5dfb8959ef3c1bd1447de80

Observation 03fada80-01ba-4d15-b22e-61cb361d52e7 · outbound

This paper cites Un- supervised learning of depth and ego-motion from monocu- lar video using 3d geometric constraints.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Un- supervised learning of depth and ego-motion from monocu- lar video using 3d geometric constraints

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:29.001140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.838684Z digest=sha256:d0f74e4955a18d7790629190a77e5510996323ab76444af7a0e7d5b76775a30a

Observation faae2d43-39ef-4749-8b86-0ef22ff4db72 · outbound

This paper cites Fish eye lens.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Fish eye lens

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.986109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.842757Z digest=sha256:0ac42c0c428a8719a553ea0a3c3ca508f05a66fab1480ae309ab6a379b84de9d

Observation 49b5f7c9-6123-4fdc-b60e-35153b73e166 · outbound

This paper cites Test- time adaptation for depth completion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Test- time adaptation for depth completion

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.969597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.846868Z digest=sha256:6529820459fff27ae2db315e20ff8c15fa67ed7f761b806a8b9b1d745c516e6a

Observation 4ff4b7b6-c0f0-4104-96c3-486aaedb0e2c · outbound

This paper cites Excavating the potential capacity of self- supervised monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Excavating the potential capacity of self- supervised monocular depth estimation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.954294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.851534Z digest=sha256:717dd78e2bc4ae271ef7d0eb15387fa493a8ffffb2fef35b0ff79517ba56c012

Observation b7cad6bd-95ca-49b7-9a98-d35612479303 · outbound

This paper cites Unidepth: Universal monocular metric depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Unidepth: Universal monocular metric depth estimation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.939493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.855621Z digest=sha256:30e2385cebc60c154431abdac6a7ac3bdd82bce40c75a66ec97b33b558d97cfb

Observation 46699f72-57c1-41b8-a8ca-ef76d181a693 · outbound

This paper cites UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T23:45:27.860377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:45:27.860377Z digest=sha256:f3e218a3c6e9a24a2c23c59f96f19ab3afd9c2918ed1faad40d4eacb63c4b001

Observation adde3f12-e5c8-479c-afb7-65509e639909 · outbound

This paper cites Learning monocular depth estimation with unsupervised trinocular as- sumptions.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Learning monocular depth estimation with unsupervised trinocular as- sumptions

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.924076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.865002Z digest=sha256:dd7abfdf76033630326fa9fe817886d3a41ae1650e6376453f23e322ea871ae9

Observation 0468e5d8-ef7a-4c93-9261-31a01c2aff6b · outbound

This paper cites On the uncertainty of self-supervised monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens On the uncertainty of self-supervised monocular depth estimation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.908950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.869501Z digest=sha256:044fa13d08f1f9dbedbdeac79de48287bde0e471c4df047ddb27fe24dc7c16f0

Observation 1fb5f5ee-578f-4aa9-9638-97f0f0948f47 · outbound

This paper cites Vi- sion transformers for dense prediction.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Vi- sion transformers for dense prediction

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.893886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.873644Z digest=sha256:cf156ab7d06be1867770b738b5090cf7b2ffb8c1f7eb28215e37f1fdf7fd7f61

Observation fbe3e9ee-0222-4195-9349-5396c82e211f · outbound

This paper cites Towards Robust Monocu- lar Depth Estimation: Mixing Datasets for Zero-Shot Cross- Dataset Transfer.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Towards Robust Monocu- lar Depth Estimation: Mixing Datasets for Zero-Shot Cross- Dataset Transfer

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.878754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.877858Z digest=sha256:2780f2d025d9c8e59117af478f080b490204ea44152174102dfe9d3565e814c4

Observation 4120eabb-abb6-4699-95d3-e53964144489 · outbound

This paper cites Radar-Guided Polynomial Fitting for Metric Depth Estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Radar-Guided Polynomial Fitting for Metric Depth Estimation

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-05T23:45:27.882070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:45:27.882070Z digest=sha256:d5bd404fb1a7a38ec0ae4565405e11be2fea817ff0419f579b7ce8364aa2506d

Observation a95ded25-8f33-44cc-a0ce-b83662bcec84 · outbound

This paper cites Protodepth: Unsupervised contin- ual depth completion with prototypes.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Protodepth: Unsupervised contin- ual depth completion with prototypes

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.864223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.887477Z digest=sha256:961387fc0ad2a8e88030036753fd6c42e0a7fcb3c5ee0c5ab6d950a6adbc5f51

Observation 6ae31da0-4d89-4c02-b08b-52b0fea3accf · outbound

This paper cites Hypersim: A photorealistic syn- thetic dataset for holistic indoor scene understanding.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Hypersim: A photorealistic syn- thetic dataset for holistic indoor scene understanding

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.849663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.891947Z digest=sha256:edd6a500402d3daefe3ba2a7bf3af10f5dd0a035df35b5166b0ef798e827081d

Observation 096a9a05-fcef-4add-8692-fe1f7b4ae123 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Indoor segmentation and support inference from rgbd images

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.834536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.896308Z digest=sha256:a589584985c5d2e4f0bc92332b5f29430fbe166cee7e444f44e22771825fb097

Observation 44ee9164-1c57-464a-a458-4a6bf585e55c · outbound

This paper cites Depth estimation from camera image and mmwave radar point cloud.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depth estimation from camera image and mmwave radar point cloud

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.819256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.900315Z digest=sha256:6e6e154807d9c0c76f4e383c4e4ae46403a2163733bc2e45b36f8408231a2f07

Observation 418221b0-553c-45d4-9667-daad2e9c8ff8 · outbound

This paper cites Nonparametric correction of distortion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Nonparametric correction of distortion

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.804069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.904369Z digest=sha256:8658e96acadd355c896ad00626044157ab96a50121a82fff95c94d6a198aba9b

Observation 2188006a-d566-4c3c-93cf-cb08f1fc7a4f · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Scalability in perception for autonomous driving: Waymo open dataset

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.789451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.908459Z digest=sha256:510569be8e107277c817368c04af35923417e96b949445e7edd34387fce36e61

Observation e349bdc4-57ba-44db-a2d0-2781d71cab8a · outbound

This paper cites Learning monocular depth estimation infusing tradi- tional stereo knowledge.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Learning monocular depth estimation infusing tradi- tional stereo knowledge

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.774874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.912457Z digest=sha256:dfd75b50a5ab585bd1498625575cdbd5457369ea7e0aec68b1559981001995a8

Observation 55ab0b5a-627e-4077-aa06-862e08ca7996 · outbound

This paper cites Training data-efficient image transformers and distillation through at- tention.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Training data-efficient image transformers and distillation through at- tention

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.760253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.916674Z digest=sha256:caccea4993713915ed1fa6b8a16ef829ec87026c97b3f1db57ef45d57c0ef1cf

Observation dc8ca9eb-b009-4ceb-8919-d642fd86f3b3 · outbound

This paper cites Enhancing diffusion models with 3d perspec- tive geometry constraints.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Enhancing diffusion models with 3d perspec- tive geometry constraints

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.745316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.921100Z digest=sha256:90f6e84307b03cebad0330315b002c2659239d953aaad6b178b5a694372bb01d

Observation e3758383-3aee-4e64-8981-83f4512222a2 · outbound

This paper cites Learning depth from monocular videos using direct methods.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Learning depth from monocular videos using direct methods

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.730155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.925244Z digest=sha256:4940fabddb95f8958a65d8aa1860e1d6b56bdcfe78af8bce8a52cc2806b8eae0

Observation ee417e1f-de91-4138-ae1b-d11282966187 · outbound

This paper cites Irs: A large naturalistic indoor robotics stereo dataset to train deep models for dis- parity and surface normal estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Irs: A large naturalistic indoor robotics stereo dataset to train deep models for dis- parity and surface normal estimation

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.716214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.929519Z digest=sha256:7a4c691879fde2a9d6967f572069369dfc78f52341666eca2578c55ce17d399c

Observation e124693d-51b5-4f94-a847-6f17ea18f715 · outbound

This paper cites Self-supervised monocular depth hints.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Self-supervised monocular depth hints

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.701065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.933627Z digest=sha256:be6186ad7b425a414bd17a0492983bf812a546d28b5e4e6bbeb0758864861d4b

Observation f222b5aa-0ff1-40d3-846c-b2f824fa3806 · outbound

This paper cites Bilateral cyclic con- straint and adaptive regularization for unsupervised monoc- ular depth prediction.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Bilateral cyclic con- straint and adaptive regularization for unsupervised monoc- ular depth prediction

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.686533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.937748Z digest=sha256:24647d9faf117dcaec8d1e4ab1a875334aff00a31d31dd3ad9d76409abfe9a4c

Observation d9cdd9ed-1574-4bf3-aca1-ceb2be592989 · outbound

This paper cites Targeted ad- versarial perturbations for monocular depth prediction.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Targeted ad- versarial perturbations for monocular depth prediction

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.671650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.941946Z digest=sha256:ecde48814d84587f86aec5756e2b16fc8cc3087cf70ce79f5bc77785468678cb

Observation 6975653f-52c0-49c4-96e9-64d094173df9 · outbound

This paper cites Unsupervised depth completion from visual iner- tial odometry.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Unsupervised depth completion from visual iner- tial odometry

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.656989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.945855Z digest=sha256:5c039f1e0b27625bfaef8146826576afeb0f68b13b06ef44cf4e83590625f086

Observation 508b3414-1f94-4cfa-a954-88f2d56b7bec · outbound

This paper cites Learning topol- ogy from synthetic data for unsupervised depth comple- tion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Learning topol- ogy from synthetic data for unsupervised depth comple- tion

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.642410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.949938Z digest=sha256:47a97a56645c4db5fd0f13d5a7b6f09e0bc9a97fece97db8cb4ee5b6e5aa2c7e

Observation 4107abfe-a4ed-4771-b27f-4338817337cf · outbound

This paper cites An adaptive framework for learning unsupervised depth completion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens An adaptive framework for learning unsupervised depth completion

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.627690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.954036Z digest=sha256:7965b591ca95a7bd0c4332206a61a2fef0dff32c7aefc272e2248f617224b965

Observation 13541b94-578d-41e1-b387-bbd196e3f07a · outbound

This paper cites Augundo: Scaling up augmentations for monocular depth completion and estima- tion.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Augundo: Scaling up augmentations for monocular depth completion and estima- tion

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.611702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.958026Z digest=sha256:e12cde6e1d3ab842b5c59f865a4ae0e2c122684014487333f1951cef688a490a

Observation 717d2e82-6b5f-4573-b284-f0d902e3fc2f · outbound

This paper cites Quadric representations for lidar odometry, mapping and localization.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Quadric representations for lidar odometry, mapping and localization

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.596165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.961915Z digest=sha256:9a02220e47e4c83bf04162fbcc037f1d3693b68a37ff357e77743295143fe116

Observation 6b6267dd-f560-4f03-9e13-d7f8f3fedf46 · outbound

This paper cites Sparsefusion: Fusing multi-modal sparse rep- resentations for multi-sensor 3d object detection.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Sparsefusion: Fusing multi-modal sparse rep- resentations for multi-sensor 3d object detection

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.581337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.965824Z digest=sha256:f6eef65bda2025b0107bab45a76b75f301852ce2ef7928d0e0fc208e8b3f7395

Observation 0a8d5f3a-e5bb-484b-917f-d4091db095c0 · outbound

This paper cites Multi-scale continuous crfs as sequential deep networks for monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Multi-scale continuous crfs as sequential deep networks for monocular depth estimation

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.566547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.969996Z digest=sha256:e8b70e1ee08a5132bf96f2b486392da05068653aa12a5f2f658baef383561932

Observation da00c7e2-03ac-47f3-a3a9-42242e75d2ca · outbound

This paper cites Binding touch to everything: Learning unified multimodal tactile rep- resentations.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Binding touch to everything: Learning unified multimodal tactile rep- resentations

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.551942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.974016Z digest=sha256:766c74a3dfe833a8d238bababbc7669e6c94052c28b3dc8047a65bef3465711c

Observation 16ca8bd2-0cdd-4a95-85f7-a0d877bf5381 · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Depth anything: Unleashing the power of large-scale unlabeled data

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.537173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.978073Z digest=sha256:98aa151181187a8f2f0708b6273203f834904d1595a1e260664c436592b1f9ba

Observation 3c6d21cc-4971-4218-bbe6-4338108a3e96 · outbound

This paper cites Dense depth posterior (ddp) from single image and sparse range.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Dense depth posterior (ddp) from single image and sparse range

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.521748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.982061Z digest=sha256:caef412c49bb6f4a16a905c6ba638356900b0525b681e1dede4fd8c07cd58463

Observation 11a0f1fc-3ab4-435e-afe0-0a8484492c3b · outbound

This paper cites Lego: Learning edge with geometry all at once by watching videos.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Lego: Learning edge with geometry all at once by watching videos

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.507172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.986215Z digest=sha256:818cdb2f482a43dd42c4828d139f3f6d152e21eb2b6c92befc92fd727869d452

Observation 6fa92d5d-7578-445c-9eb8-40d2ad8ba984 · outbound

This paper cites Scannet++: A high-fidelity dataset of 3d in- door scenes.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Scannet++: A high-fidelity dataset of 3d in- door scenes

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.492224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.990198Z digest=sha256:84a8e799ea9af56e9fcd61265c81e508395269fc3d6637654e20b5815ee04e4a

Observation f85fb2af-c23f-4f70-a8c3-9534c585fe84 · outbound

This paper cites En- forcing geometric constraints of virtual normal for depth pre- diction.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens En- forcing geometric constraints of virtual normal for depth pre- diction

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.477122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.994465Z digest=sha256:bfef6678a70638f4737ced713b372a2797d8be941095d248d2ab6a455c9b17d4

Observation 50c4295a-893d-4c8a-ac49-aa2f308d4d19 · outbound

This paper cites Fisheyerecnet: A multi-context collaborative deep network for fisheye image rectification.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Fisheyerecnet: A multi-context collaborative deep network for fisheye image rectification

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.461768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:27.998585Z digest=sha256:2d875a6a769949392fefe53ccd7ee3aa213b0077ffcb49c8a4ab9e38b3852be4

Observation c48fbcec-9038-4cfb-a942-5b7bb557263e · outbound

This paper cites Fisheyebevseg: Surround view fisheye cameras based bird’s-eye view segmentation for au- tonomous driving.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Fisheyebevseg: Surround view fisheye cameras based bird’s-eye view segmentation for au- tonomous driving

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.446564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.002752Z digest=sha256:0868f6ab5ecdfee59e53eefa26ca93a24f2c4597c4c051a0c8bb192f92444e4a

Observation 8fa098d3-0e7c-4620-bc81-c9f2cfd27c78 · outbound

This paper cites Neural window fully-connected crfs for monocu- lar depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Neural window fully-connected crfs for monocu- lar depth estimation

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.431419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.006754Z digest=sha256:4ca69defce718eb502df224fb676763cca00fd8dfd24ac583c7e80e5c3effa5a

Observation b923b4ad-3269-47f7-bfe9-7cf27fb7bd8a · outbound

This paper cites Priordiffusion: Leverage language prior in diffu- sion models for monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Priordiffusion: Leverage language prior in diffu- sion models for monocular depth estimation

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-05T23:45:28.010620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:45:28.010620Z digest=sha256:0ca55108c55f9540374786e31ac9759f7ef6e65e0037e385a339a6df55150e6d

Observation 4d7502d3-6536-4e57-955f-b90a3a993587 · outbound

This paper cites Wordepth: Vari- ational language prior for monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Wordepth: Vari- ational language prior for monocular depth estimation

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.415289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.015121Z digest=sha256:feba2d47c3a0441c0a8b72c563f327263be828d32bae03d118b9cbb705b7705c

Observation b4f176bf-7395-4808-b916-46edcdd0109e · outbound

This paper cites Rsa: Resolving scale ambiguities in monoc- ular depth estimators through language descriptions.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Rsa: Resolving scale ambiguities in monoc- ular depth estimators through language descriptions

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.397762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.019716Z digest=sha256:4b52be9c627161b6a1716305ef1166f1276379b5a9a2c1c3478320657927a358

Observation b1237677-1b34-4579-8e7c-67641918fd10 · outbound

This paper cites Unsupervised learn- ing of monocular depth estimation and visual odometry with deep feature reconstruction.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Unsupervised learn- ing of monocular depth estimation and visual odometry with deep feature reconstruction

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.382264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.024049Z digest=sha256:413a79a20ac1a0a437e88a66c3cc1874cd3f29eaa432d983b99a159b6a4f4f00

Observation b82f2b9b-9883-442d-a295-aa812ca6c041 · outbound

This paper cites Lite-mono: A lightweight cnn and transformer architecture for self-supervised monocular depth estimation.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Lite-mono: A lightweight cnn and transformer architecture for self-supervised monocular depth estimation

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.366086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.028224Z digest=sha256:723a04e81a08b6aae2c302f6585a3b6474f208d9cb280560dd02e1f113e68c51

Observation 12ee8dcd-b544-40b1-bf8c-a22c399fb49a · outbound

This paper cites Monovit: Self-supervised monocular depth estimation with a vision transformer.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Monovit: Self-supervised monocular depth estimation with a vision transformer

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.350138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.032630Z digest=sha256:9f54fd1099ba4d9c369b55b2d269b287d089b1fce992e87b7209020d7501770f

Observation 2591e395-fdc9-4648-93ed-649ea149a748 · outbound

This paper cites FisheyeDepth: A Real Scale Self-Supervised Depth Estimation Model for Fisheye Camera.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens FisheyeDepth: A Real Scale Self-Supervised Depth Estimation Model for Fisheye Camera

Reference 88

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:45:28.086832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.036835Z digest=sha256:59d0f21e7bbfe6f3530e8a687955bbe7b7e77fee818b372b931570dbd84ec75e

Observation aec8a0ca-f9bf-4af8-ac27-7c82d6ad3091 · outbound

This paper cites Unsupervised learning of depth and ego-motion from video.

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens Unsupervised learning of depth and ego-motion from video

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T23:45:28.332880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T23:45:28.041206Z digest=sha256:3e35e3e916d71fd07462a2324071de166968eb57e025bbd94b853126907f57f6

Pith citing papers

No inbound Pith citation observations are available.