Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens | Paper Citation Record

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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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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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This paper cites Memory Transformer.

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

Reference 4

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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 2026-08-09T06:31:02.800959+00:00.

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