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Paper Citation Record · LEDGER

Learning Inverse Laplacian Pyramid for Progressive Depth Completion

As of 20 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 2 inbound Pith citation observations for arXiv:2502.07289.

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

pith.paper-citation-record.v1
2502.07289 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:16:55.366759Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:19:13.643985Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T13:55:53.211660Z

Reference resolution

59 of 59 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ddd7308-714e-42cb-8f92-67c3e4474d14 · outbound

This paper cites Hybrid-mvs: Robust multi-view reconstruction with hybrid optimization of visual and depth cues,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Hybrid-mvs: Robust multi-view reconstruction with hybrid optimization of visual and depth cues,

Reference 1

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Observation 016c1a2b-1e10-4ded-9135-04a9463ec950 · outbound

This paper cites Altnerf: Learning robust neural radiance field via alternating depth-pose optimization,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Altnerf: Learning robust neural radiance field via alternating depth-pose optimization,

Reference 2

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Observation 8f14053d-aebd-4b47-8d68-e1e98d8d5f7f · outbound

This paper cites A low-cost and scalable framework to build large-scale localization benchmark for augmented reality,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion A low-cost and scalable framework to build large-scale localization benchmark for augmented reality,

Reference 3

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Observation 9dc0f196-55f2-45d3-aac4-423aaff2ea76 · outbound

This paper cites Designing for depth perceptions in augmented reality,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Designing for depth perceptions in augmented reality,

Reference 4

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Source-reported events for the cited work

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Observation e4195319-7f62-4ef8-b6d1-0ed63728b71e · outbound

This paper cites Digital video stabilization method based on periodic jitters of airborne vision of large flapping wing robots,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Digital video stabilization method based on periodic jitters of airborne vision of large flapping wing robots,

Reference 5

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Source-reported events for the cited work

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Observation f2574d3e-0a96-416d-ac2c-bbf757b56552 · outbound

This paper cites Towards real-time monocular depth estimation for robotics: A survey,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Towards real-time monocular depth estimation for robotics: A survey,

Reference 6

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Observation 6c6489b3-e638-4646-be45-89aa54e54922 · outbound

This paper cites Sparse-to- dense depth estimation in videos via high-dimensional tensor voting,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Sparse-to- dense depth estimation in videos via high-dimensional tensor voting,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0175ce54-59d1-4913-9103-c51ca2ad1f42 · outbound

This paper cites Dcdepth: Progressive monocular depth estimation in discrete cosine domain,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Dcdepth: Progressive monocular depth estimation in discrete cosine domain,

Reference 8

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Source-reported events for the cited work

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Observation 2a9d299c-3ed1-47b0-bca0-49b7399162e4 · outbound

This paper cites Regularizing nighttime weirdness: Efficient self-supervised monocular depth estimation in the dark,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Regularizing nighttime weirdness: Efficient self-supervised monocular depth estimation in the dark,

Reference 9

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Observation 0a140de4-5cf2-477b-8c5b-f3c9547f1081 · outbound

This paper cites Depth- centric dehazing and depth-estimation from real-world hazy driving video,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Depth- centric dehazing and depth-estimation from real-world hazy driving video,

Reference 10

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Observation 1eee76d9-a777-4486-9cc6-f826815d3501 · outbound

This paper cites Sgnet: Structure guided network via gradient-frequency awareness for depth map super-resolution,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Sgnet: Structure guided network via gradient-frequency awareness for depth map super-resolution,

Reference 11

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Source-reported events for the cited work

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Observation d533f053-2c58-4dca-b2e2-d36ffefaed9c · outbound

This paper cites Deep depth completion of a single rgb-d image,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Deep depth completion of a single rgb-d image,

Reference 14

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Source-reported events for the cited work

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Observation 1f09fc28-1dda-4b60-b3ff-b5c100d79581 · outbound

This paper cites Learning depth with convolutional spatial propagation network,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Learning depth with convolutional spatial propagation network,

Reference 15

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Source-reported events for the cited work

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Observation 4dbec7e1-9057-4be4-a786-48e548ae072e · outbound

This paper cites Non-local spatial propagation network for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Non-local spatial propagation network for depth completion,

Reference 16

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Source-reported events for the cited work

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Observation efc0e91f-1985-41c4-b3f2-d435f686a160 · outbound

This paper cites Rignet: Repetitive image guided network for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Rignet: Repetitive image guided network for depth completion,

Reference 18

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Source-reported events for the cited work

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Observation 5d0a2357-b46b-430e-ae7d-af25c32395b1 · outbound

This paper cites Cspn++: Learning context and resource aware convolutional spatial propagation networks for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Cspn++: Learning context and resource aware convolutional spatial propagation networks for depth completion,

Reference 19

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Observation 2b4b3b26-b7eb-4122-9858-a040e5bac518 · outbound

This paper cites Dyspn: Learning dy- namic affinity for image-guided depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Dyspn: Learning dy- namic affinity for image-guided depth completion,

Reference 20

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Source-reported events for the cited work

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Observation 89c02ff8-6de8-403d-82fe-bf0eb4033c85 · outbound

This paper cites Depth seeds: Recovering incomplete depth data using superpixels,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Depth seeds: Recovering incomplete depth data using superpixels,

Reference 21

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Source-reported events for the cited work

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Observation ef8c9ab4-6631-4244-a2e6-b5632fa2cdab · outbound

This paper cites Seeds: Superpixels extracted via energy-driven sampling,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Seeds: Superpixels extracted via energy-driven sampling,

Reference 22

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Source-reported events for the cited work

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Observation e5a4023c-e733-4fba-bb28-d890eb2745d4 · outbound

This paper cites In defense of classical image processing: Fast depth completion on the cpu,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion In defense of classical image processing: Fast depth completion on the cpu,

Reference 23

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Source-reported events for the cited work

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Observation 8d0bce8f-1cae-48c4-ab39-4c42d5b93d71 · outbound

This paper cites A surface geometry model for lidar depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion A surface geometry model for lidar depth completion,

Reference 24

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Observation eb9e6761-33db-45a6-837b-d96a57522126 · outbound

This paper cites Sparsity invariant cnns,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Sparsity invariant cnns,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0ee62c98-6a6b-42ba-8692-688824a9c163 · outbound

This paper cites Hms- net: Hierarchical multi-scale sparsity-invariant network for sparse depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Hms- net: Hierarchical multi-scale sparsity-invariant network for sparse depth completion,

Reference 26

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Source-reported events for the cited work

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Observation a532d2d0-cad1-4550-aa8a-2de04ec0bbfd · outbound

This paper cites Uncertainty- aware cnns for depth completion: Uncertainty from beginning to end,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Uncertainty- aware cnns for depth completion: Uncertainty from beginning to end,

Reference 27

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Source-reported events for the cited work

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Observation acf3bb9e-c067-4f3d-b4a6-6dda013f47b3 · outbound

This paper cites Estimat- ing depth from rgb and sparse sensing,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Estimat- ing depth from rgb and sparse sensing,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 943c8196-ed0b-4f96-bda7-d96c7e48cc03 · outbound

This paper cites Learning steering kernels for guided depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Learning steering kernels for guided depth completion,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8c707a89-2170-4971-b072-65e1aa0946e4 · outbound

This paper cites Bilateral propagation network for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Bilateral propagation network for depth completion,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5ab22e4f-ea1d-4fc6-b8c5-43a12f4ecbc9 · outbound

This paper cites Learning joint 2d- 3d representations for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Learning joint 2d- 3d representations for depth completion,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9e4740b1-8f1e-43b0-ba9a-686e5ce030c3 · outbound

This paper cites Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 56b7d4d9-447b-4400-a284-85ba6c4c619f · outbound

This paper cites Learning guided convolutional network for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Learning guided convolutional network for depth completion,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 29f20205-7d10-4fc7-aa09-ef849bb2d8b3 · outbound

This paper cites Guideformer: Transformers for image guided depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Guideformer: Transformers for image guided depth completion,

Reference 34

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1c699943-abca-4c12-b600-b0fa89df38e1 · outbound

This paper cites Bev@dc: Bird’s-eye view assisted training for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Bev@dc: Bird’s-eye view assisted training for depth completion,

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 317cd449-3501-4c10-b5a6-cdc58bff34c3 · outbound

This paper cites Tri-perspective view decomposition for geometry-aware depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Tri-perspective view decomposition for geometry-aware depth completion,

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e142d01f-d3f2-415f-a011-456301cbd564 · outbound

This paper cites Dynamic spatial propagation network for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Dynamic spatial propagation network for depth completion,

Reference 37

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raw_fallback, observed 2026-08-08T13:16:55.784966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.243865Z digest=sha256:7289a40c4252be950adb3e6f5d47112acdeb693764105320932b112844b07df5

Observation 8f9bef56-e8ae-40a9-9f30-a5dc599fc42c · outbound

This paper cites Graphcspn: Geometry- aware depth completion via dynamic gcns,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Graphcspn: Geometry- aware depth completion via dynamic gcns,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.768896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.248780Z digest=sha256:5574b841e620b9951589261b45ec40dba53ca253931eaf23c60c9708fe5a546e

Observation 0bed2f6d-d5c7-45e5-83cc-58d23bc7a4f4 · outbound

This paper cites Lrru: Long- short range recurrent updating networks for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Lrru: Long- short range recurrent updating networks for depth completion,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.752063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.253377Z digest=sha256:cda59c994ba5e9879a87502c558cb1c60732cf1599681b8a9a42f103423f9c22

Observation 5f85e94d-59a9-4d17-a66a-20085aa56c32 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion U-net: Convolutional networks for biomedical image segmentation,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T13:16:55.258484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:16:55.258484Z digest=sha256:fb13bcb0b72a48bb8ff9ef70822a57b1ba9103aaedd61f9d1c0c70d2b7a454b7

Observation a1dee641-a4bd-439e-a6f0-e83d0e94523e · outbound

This paper cites Deep residual learning for image recognition,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Deep residual learning for image recognition,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T13:16:55.262938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:16:55.262938Z digest=sha256:4e41d41f4959f31c10af4e629ec06d9b6951fc04cc7ca16b6e76129695c740bb

Observation 456a9257-d3bb-41f5-b4a7-237911442bd4 · outbound

This paper cites Improving depth completion via depth feature upsampling,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Improving depth completion via depth feature upsampling,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.714914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.267719Z digest=sha256:3d05dcc5143e996150749444c5a09a26544a3b5f7708681979a5d42abf36e27e

Observation 48c9af89-65d8-4ede-b7b3-2af10bbb7c51 · outbound

This paper cites Deformable convolutional networks,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Deformable convolutional networks,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.699369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.272526Z digest=sha256:9fd6e4bab3171f47f891d94b5e6017254e48c4f91beea89a2b2d2bbcf0398120

Observation 5bb473d6-3993-4fb7-85b4-783f34e78523 · outbound

This paper cites Deformable convnets v2: More deformable, better results,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Deformable convnets v2: More deformable, better results,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.683776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.277345Z digest=sha256:38506526670be07852836400c518a3b1552f90591b8e59999a6cc521a89e3dfd

Observation 8030c225-69af-4868-9535-07182a300534 · outbound

This paper cites Sparse-to-dense: Depth prediction from sparse depth samples and a single image,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Sparse-to-dense: Depth prediction from sparse depth samples and a single image,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.668113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.282146Z digest=sha256:33b372172fb1111f02382064bba4f69d7c1a9021c4f8674ae56285c1631c977c

Observation 15406925-986f-4118-96d7-0824f6c3d8ee · outbound

This paper cites Confidence propagation through cnns for guided sparse depth regression,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Confidence propagation through cnns for guided sparse depth regression,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.652079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.287086Z digest=sha256:ac0e61399a43590d2ff926a92848e39796f4425fc8309d189aec23b9c61522b5

Observation 9ab69975-f163-4343-8115-cbdb77237403 · outbound

This paper cites Depth completion with twin surface extrapolation at occlusion boundaries,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Depth completion with twin surface extrapolation at occlusion boundaries,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.634845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.291963Z digest=sha256:5f739f972907ce609bb782aa38261cbc3eccffeca6c81472a09655f13b8c19a8

Observation 3f960fa1-1661-4dba-9e12-15a61ccefb3a · outbound

This paper cites Adaptive context-aware multi- modal network for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Adaptive context-aware multi- modal network for depth completion,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.618744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.296732Z digest=sha256:4f114b89a20700e6a1459aec6bf0c77e7d7d08d9a026dfae8ffd2961c89d818e

Observation 0ef5b65d-6672-4a15-8686-3dea638109e1 · outbound

This paper cites Fcfr-net: Feature fusion based coarse-to-fine residual learning for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Fcfr-net: Feature fusion based coarse-to-fine residual learning for depth completion,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.603028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.301698Z digest=sha256:3ab0da8bbc9dd119a9b6e0cb7159219471e4ca84e3e0e6ece0ac8163d394f262

Observation 53b3c897-ee2c-4b68-a032-0bc610f833b3 · outbound

This paper cites Penet: Towards precise and efficient image guided depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Penet: Towards precise and efficient image guided depth completion,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.585674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.307262Z digest=sha256:1f2f98d99b1ffeecee214e007a9c850df5b6479ec1d8e84dd0beaf3276768f24

Observation 6b4c8ddf-1919-4d00-934b-72e5a14b13bd · outbound

This paper cites Completionformer: Depth completion with convolutions and vision transformers,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Completionformer: Depth completion with convolutions and vision transformers,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.567757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.312686Z digest=sha256:52eaf6ce923f386a7090364f705db1639eb8f8a48b3cf58fcd88256e6a438ecd

Observation 406a8b62-542a-4637-a936-995679991588 · outbound

This paper cites Decomposed guided dynamic filters for efficient rgb-guided depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Decomposed guided dynamic filters for efficient rgb-guided depth completion,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:56.079102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.317526Z digest=sha256:c351997b3aa8288ece99816b94d659af23b10e0f813312bc859d8406724caed6

Observation 5a034338-1775-4a2d-8656-c8bfab5ecfc1 · outbound

This paper cites Ogni-dc: Robust depth completion with optimization-guided neural iterations,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Ogni-dc: Robust depth completion with optimization-guided neural iterations,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.550518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.322096Z digest=sha256:71fc792a43ada71c4a0070925cd349fed4bb3ab983ce2699bca3685307512cce

Observation c333efdd-0976-45d4-a898-2cb09bb1e4cb · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.532201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.327097Z digest=sha256:4664235fbeb4bb5f5b53cb65eeded49af67e0078059f9297b7da6f1cad67827e

Observation d77012fc-56d7-4263-a2f3-af508d876f51 · outbound

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

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Indoor segmentation and support inference from rgbd images,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.515646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.331723Z digest=sha256:02d97633e0cd70803e8b703b20d74552ae5392cc0d4ac0c16f642f5bf02cfd4d

Observation 5cf48079-a2be-4532-a9c9-d9aa580474a9 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Pytorch: An imperative style, high-performance deep learning library,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.498483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.336918Z digest=sha256:3ce870b0fd736b3ec2deb1b130e4ee6d46d6920c0d7d9b1ab4c2affcc1172940

Observation 19a0e87a-c676-4eb3-9b44-ac0e077c04e1 · outbound

This paper cites FractalNet: Ultra-Deep Neural Networks without Residuals.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion FractalNet: Ultra-Deep Neural Networks without Residuals

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T13:16:55.341820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:16:55.341820Z digest=sha256:0267582bf95bc50d4f9a16223ce21ab7c1052bac6876a855d9fef3830e418e40

Observation 02f55804-d1f3-4ba4-acdb-c6a5a2385d99 · outbound

This paper cites Decoupled weight decay regularization,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Decoupled weight decay regularization,

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-08T13:16:55.346963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:16:55.346963Z digest=sha256:778a25343a3f107ea0ee6131d9f49c06f4faa34ecad3dda9c844aab664ab6715

Observation ffd7635d-88c4-49c5-993a-67fdaa6798a8 · outbound

This paper cites Super-convergence: Very fast training of neural networks using large learning rates,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Super-convergence: Very fast training of neural networks using large learning rates,

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-08T13:16:55.351586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:16:55.351586Z digest=sha256:a0efbd121dd37e10444615f5fb985c16e809a8f01f9540f4770cef2908bbf4d0

Observation 21ae7623-f06c-4487-9790-fe7b4a3ce842 · outbound

This paper cites Aggregating feature point cloud for depth completion,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Aggregating feature point cloud for depth completion,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.460191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.357145Z digest=sha256:1e99562429b21f12ea1cb0fad8d93fd774d5e6b02df6658789265f7c62dad7c5

Observation 8930fd33-63da-4a86-8a4c-493996bfad17 · outbound

This paper cites Sparse and noisy lidar completion with rgb guidance and uncertainty,.

Learning Inverse Laplacian Pyramid for Progressive Depth Completion Sparse and noisy lidar completion with rgb guidance and uncertainty,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.443014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.361656Z digest=sha256:9d9973a5cef2e963e2dfac5f1176fb051923e8ef688385b3f9e27767d777a2e5

Observation 44b21de9-a2ef-458a-b311-faf60677f8d6 · outbound

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

Learning Inverse Laplacian Pyramid for Progressive Depth Completion An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T13:16:55.425439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-08T13:16:55.366759Z digest=sha256:913e2e9aaeb82fa542eb9b425c0336fe6d8ba8f01851798901053af661ccabd4

Pith citing papers

Observation 26d0614a-9d5b-4469-9369-5003e5b45a52 · inbound

Event-Driven Dynamic Scene Depth Completion cites this paper.

Event-Driven Dynamic Scene Depth Completion Learning Inverse Laplacian Pyramid for Progressive Depth Completion

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T20:19:13.643985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:19:13.643985Z digest=sha256:ef63a57c2a12d2e93ef843bf2f1db968134367e522fdbbf0f12dac5c36068b34

Observation 5db3ed3a-644d-4a0b-80c9-36b038b2e7a2 · inbound

Need for Speed: Zero-Shot Depth Completion with Single-Step Diffusion cites this paper.

Need for Speed: Zero-Shot Depth Completion with Single-Step Diffusion Learning Inverse Laplacian Pyramid for Progressive Depth Completion

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:55:53.213639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T13:52:01.152288Z digest=sha256:18af1cb5d5d3e4cd26b60d159cf1c79308760b66ba3b99ba8d468463d3e7bac8