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Paper Citation Record · LEDGER

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network

As of 10 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2507.11333.

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

pith.paper-citation-record.v1
2507.11333 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:17:32.245045Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

52 of 52 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c4139bc9-0e69-4265-8aaf-baca73988b9a · outbound

This paper cites Large-scale data for multiple-view stereopsis.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Large-scale data for multiple-view stereopsis

Reference 1

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Observation d15fb55e-746c-4f43-b28d-d4444595194d · outbound

This paper cites Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Reference 2

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Observation 1c3e58f2-ef25-482e-860d-96266ec81a1d · outbound

This paper cites Mvsformer: Multi-view stereo by learning robust image features and temperature-based depth.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Mvsformer: Multi-view stereo by learning robust image features and temperature-based depth

Reference 3

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Observation f17fe654-93c0-4aa6-8026-86e6424b9173 · outbound

This paper cites MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo

Reference 4

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Observation 27ae1490-dd7b-4989-aa65-9f166ba27922 · outbound

This paper cites Deep stereo using adap- tive thin volume representation with uncertainty awareness.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Deep stereo using adap- tive thin volume representation with uncertainty awareness

Reference 5

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Observation d9b5b3db-48a0-4bd8-9175-d69982224459 · outbound

This paper cites Twins: Revisiting the design of spatial attention in vision transformers.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Twins: Revisiting the design of spatial attention in vision transformers

Reference 6

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Observation 8b5499f1-8b50-4c86-9ac1-f7b01e789f28 · outbound

This paper cites Deformable convolutional networks.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Deformable convolutional networks

Reference 7

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Source-reported events for the cited work

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Observation c31e7eb2-e47e-4de1-a4e7-c0cee7dc17b2 · outbound

This paper cites Transmvs- net: Global context-aware multi-view stereo network with transformers.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Transmvs- net: Global context-aware multi-view stereo network with transformers

Reference 8

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Observation e84e4600-8003-4f91-a89c-4241b532440b · outbound

This paper cites Massively parallel multiview stereopsis by surface normal diffusion.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Massively parallel multiview stereopsis by surface normal diffusion

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6ec202e9-08df-4ca5-8750-54f4c6e37780 · outbound

This paper cites Cascade cost volume for high-resolution multi-view stereo and stereo matching.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Cascade cost volume for high-resolution multi-view stereo and stereo matching

Reference 10

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Observation 7096917f-9406-4626-a233-970f8dd86128 · outbound

This paper cites Group-wise correlation stereo network.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Group-wise correlation stereo network

Reference 11

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Source-reported events for the cited work

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Observation b149861f-5e46-4e67-bd99-5409049ae74e · outbound

This paper cites Squeeze-and-excitation net- works.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Squeeze-and-excitation net- works

Reference 12

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Observation 9b4d8a1e-e59e-4712-bf1f-3287403f5af0 · outbound

This paper cites Di-mvs: Learning efficient multi-view stereo with depth- aware iterations.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Di-mvs: Learning efficient multi-view stereo with depth- aware iterations

Reference 13

Resolution
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Source-reported events for the cited work

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Observation ea2d48f2-96de-4fc9-833d-077281a6a341 · outbound

This paper cites Rrt-mvs: Recurrent regular- ization transformer for multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Rrt-mvs: Recurrent regular- ization transformer for multi-view stereo

Reference 14

Resolution
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2042e068-4d99-4107-9c20-8b9360d20a1f · outbound

This paper cites Parallel feature pyra- mid network for object detection.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Parallel feature pyra- mid network for object detection

Reference 15

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d59e0f59-b472-4938-9a37-2b103088e368 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Adam: A Method for Stochastic Optimization

Reference 16

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Observation f06eb88c-4873-4997-84c1-d886140450a5 · outbound

This paper cites Tanks and temples: Benchmarking large-scale scene reconstruction.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Tanks and temples: Benchmarking large-scale scene reconstruction

Reference 17

Resolution
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Source-reported events for the cited work

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Observation 3f8953db-a50f-4976-8ac2-0bb782c4af77 · outbound

This paper cites Learning deformable hypothesis sampling for ac- curate patchmatch multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Learning deformable hypothesis sampling for ac- curate patchmatch multi-view stereo

Reference 18

Resolution
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Observation 75dd8244-0ce9-4d0f-8162-404cea980fa6 · outbound

This paper cites Wt-mvsnet: window-based transformers for multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Wt-mvsnet: window-based transformers for multi-view stereo

Reference 19

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Observation 76f6d468-5af4-43fe-88be-fd7b76266116 · outbound

This paper cites Protocar: Learning 3d vehicle prototypes from single-view and unconstrained driving scene images.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Protocar: Learning 3d vehicle prototypes from single-view and unconstrained driving scene images

Reference 20

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Observation 0c017487-385e-4e59-a2ce-40464d82cd13 · outbound

This paper cites When epipolar constraint meets non-local oper- ators in multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network When epipolar constraint meets non-local oper- ators in multi-view stereo

Reference 21

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Observation 65b8af3e-b006-4868-a340-924b4cadf03f · outbound

This paper cites Generalized binary search network for highly-efficient multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Generalized binary search network for highly-efficient multi-view stereo

Reference 22

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Observation ab18630e-676e-4706-a655-529dbb7dee69 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network DINOv2: Learning Robust Visual Features without Supervision

Reference 23

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Observation 4db9ccf6-f2e1-4702-aa6f-57bfc8865860 · outbound

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

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Pytorch: An im- perative style, high-performance deep learning library

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ace0fc28-2a04-4745-8974-6f42e8d89cc7 · outbound

This paper cites Rethinking depth estimation for multi- view stereo: A unified representation.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Rethinking depth estimation for multi- view stereo: A unified representation

Reference 25

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Observation 05d7d923-bdec-41d7-8c4c-b9268a9d7ef7 · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer

Reference 26

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Observation 6701989b-9751-45f5-b794-aeddbb068798 · outbound

This paper cites Vi- sion transformers for dense prediction.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Vi- sion transformers for dense prediction

Reference 27

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Observation fc755e74-efb6-4ff8-b008-47638e53b7d5 · outbound

This paper cites Pixelwise view selection for unstructured multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Pixelwise view selection for unstructured multi-view stereo

Reference 28

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Source-reported events for the cited work

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Observation 21cc745d-3e81-4550-9452-e782095fabf1 · outbound

This paper cites Tiny and efficient model for the edge detec- tion generalization.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Tiny and efficient model for the edge detec- tion generalization

Reference 29

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Source-reported events for the cited work

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Observation a3a3fc70-de6e-4f00-9ae5-63cf0571edd6 · outbound

This paper cites Attention is all you need.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Attention is all you need

Reference 30

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Observation f9645ca4-dd05-41d1-9e23-46e24f45a03b · outbound

This paper cites Is-mvsnet: importance sampling-based mvsnet.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Is-mvsnet: importance sampling-based mvsnet

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8fca9d97-0e43-4b81-bd39-18d92157ca26 · outbound

This paper cites Mvster: Epipo- lar transformer for efficient multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Mvster: Epipo- lar transformer for efficient multi-view stereo

Reference 32

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raw_fallback, observed 2026-08-06T17:17:35.283859Z

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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Observation bc5b8dbb-59f9-49a8-ba76-7a265234633c · outbound

This paper cites Aa-rmvsnet: Adaptive aggregation recurrent multi-view stereo network.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Aa-rmvsnet: Adaptive aggregation recurrent multi-view stereo network

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4b54a7c0-579d-4e9f-aa43-6c2d28dcbf39 · outbound

This paper cites Gomvs: Geometrically consistent cost aggregation for multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Gomvs: Geometrically consistent cost aggregation for multi-view stereo

Reference 34

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raw_fallback, observed 2026-08-06T17:17:35.012134Z

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.

source=pdf_text observed=2026-08-06T17:17:30.843759Z digest=sha256:a74b554e484742e1e0e12040f2256005c2acf3b3a29b7dcab00c9cdd1a214cd3

Observation 5bbe2792-a323-4da3-8f9b-608082051c15 · outbound

This paper cites Planar prior assisted patch- match multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Planar prior assisted patch- match multi-view stereo

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:34.842250Z

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.

source=pdf_text observed=2026-08-06T17:17:30.907209Z digest=sha256:0ff84c15dc14e70ed25e05a8e5372c183e395f2aa7f2b2ed7aa529540637d170

Observation 39fb822c-0bd3-4012-86ad-1a2e1b1e390e · outbound

This paper cites Learning inverse depth re- gression for multi-view stereo with correlation cost volume.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Learning inverse depth re- gression for multi-view stereo with correlation cost volume

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:34.695470Z

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.

source=pdf_text observed=2026-08-06T17:17:30.920607Z digest=sha256:2ff72736b47319af83d00451729594590a32bdf6df9678237e766dff11635a37

Observation 8765179e-9369-471c-b735-d93b52db53ec · outbound

This paper cites Multi-scale geometric consistency guided and planar prior assisted multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Multi-scale geometric consistency guided and planar prior assisted multi-view stereo

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:34.561017Z

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.

source=pdf_text observed=2026-08-06T17:17:30.990450Z digest=sha256:06be42658b341d28c69281fa3c6a84e49514a888d66648cdc68aa0fcb8fc0512

Observation b1e3a4bd-7aab-49ac-a8f4-c5f6d31ab3ce · outbound

This paper cites Dense hybrid recurrent multi-view stereo net with dy- namic consistency checking.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Dense hybrid recurrent multi-view stereo net with dy- namic consistency checking

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:34.445035Z

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.

source=pdf_text observed=2026-08-06T17:17:31.057729Z digest=sha256:4dd7641c1b16443b1917f223b99b4c41b919eeeb93db8d55e4982974554ab02f

Observation 8e153339-ffb7-406b-9fd3-71b54a9dcbc6 · outbound

This paper cites Cost volume pyramid based depth inference for multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Cost volume pyramid based depth inference for multi-view stereo

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:34.316966Z

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.

source=pdf_text observed=2026-08-06T17:17:31.161135Z digest=sha256:649a62a174dade0473d2374775a503a8e5c11ed227a7036596f7c3c83f456997

Observation 7fa8af9d-3023-4ccd-957a-12f1bf68fcee · outbound

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

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Depth anything: Unleashing the power of large-scale unlabeled data

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:34.163174Z

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.

source=pdf_text observed=2026-08-06T17:17:31.222192Z digest=sha256:3b18cb7b542212237508678b48c3ad0ee8b1210d6b067db78dd70590637638fe

Observation dd16ef2e-1a10-4939-a4ae-fead146a9c6d · outbound

This paper cites Depth Anything V2.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Depth Anything V2

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T17:17:31.333515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:17:31.333515Z digest=sha256:a0eb7d7bfb930f6c0c3cfae687bbd3f17759bcbf6fa11f9289ae81fc0e8d8a16

Observation 5f830dfd-28d4-4e43-9d8a-523a03ac4867 · outbound

This paper cites Mvsnet: Depth inference for unstructured multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Mvsnet: Depth inference for unstructured multi-view stereo

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.952635Z

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.

source=pdf_text observed=2026-08-06T17:17:31.421938Z digest=sha256:d171805c81cd418ff62ec208c83f3319d35af92ce911c2819bf6ec709f4d70ce

Observation 2d569f9e-0510-472a-88e5-5dadae7f6d67 · outbound

This paper cites Recurrent mvsnet for high-resolution multi-view stereo depth inference.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Recurrent mvsnet for high-resolution multi-view stereo depth inference

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.864740Z

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.

source=pdf_text observed=2026-08-06T17:17:31.507570Z digest=sha256:bf014778323255f96730f43da32a65d663351b90ff7b65083e32f164899068e5

Observation 265ba8d2-f358-43a3-9d35-3428c932f6a1 · outbound

This paper cites Blendedmvs: A large- scale dataset for generalized multi-view stereo networks.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Blendedmvs: A large- scale dataset for generalized multi-view stereo networks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.699073Z

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.

source=pdf_text observed=2026-08-06T17:17:31.590470Z digest=sha256:467b5f69c82d8ca710baa451cde7706c966993c48adba921593209da956a93dc

Observation b13250c3-03b7-4e35-bcf7-b563523aac86 · outbound

This paper cites Constraining depth map geometry for multi-view stereo: A dual-depth approach with saddle- shaped depth cells.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Constraining depth map geometry for multi-view stereo: A dual-depth approach with saddle- shaped depth cells

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.575484Z

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.

source=pdf_text observed=2026-08-06T17:17:31.693408Z digest=sha256:46e5312ed064dc31dbc927005433c7e42c45f454a0b4746b3f721d1a88c452cf

Observation aa8fd165-bba6-4dd8-9d57-faee2fa0fd79 · outbound

This paper cites Get3dgs: Generate 3d gaussians based on points deformation fields.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Get3dgs: Generate 3d gaussians based on points deformation fields

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.453969Z

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.

source=pdf_text observed=2026-08-06T17:17:31.743757Z digest=sha256:7f502d71e2f8c56dd48bc7dff525186a4b3d62711ea196387b18030bf9054bad

Observation 80d48bd0-aa67-406e-8ea0-13f40544078c · outbound

This paper cites Msp-mvs: Multi- granularity segmentation prior guided multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Msp-mvs: Multi- granularity segmentation prior guided multi-view stereo

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.268227Z

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.

source=pdf_text observed=2026-08-06T17:17:31.820887Z digest=sha256:58a926a4d9f9c89f342823bc8be9006efe437a4a174a5281e350626466bc1f06

Observation e3406e6c-b3cd-48b1-a09d-0a1c90c804ee · outbound

This paper cites Dvp-mvs: Synergize 10 depth-edge and visibility prior for multi-view stereo.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Dvp-mvs: Synergize 10 depth-edge and visibility prior for multi-view stereo

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:33.123945Z

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.

source=pdf_text observed=2026-08-06T17:17:31.919882Z digest=sha256:4063dc7e9b621fb4d9f470f6c96e8b3b972d8a5c5167c75cbcc935104d1e06ee

Observation 1a2b918b-8d29-4058-b78d-6201bb7a7d70 · outbound

This paper cites Sed-mvs: Segmentation-driven and edge- aligned deformation multi-view stereo with depth restoration and occlusion constraint.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Sed-mvs: Segmentation-driven and edge- aligned deformation multi-view stereo with depth restoration and occlusion constraint

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:32.991852Z

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.

source=pdf_text observed=2026-08-06T17:17:32.011097Z digest=sha256:6d07fb102c036e0b4f49de7f900045e4c5b42677725879e068ffe46973fa8785

Observation e13ab05e-a860-45eb-a591-8319bcacbce2 · outbound

This paper cites Multi-view stereo representation revist: Region-aware mvsnet.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Multi-view stereo representation revist: Region-aware mvsnet

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:32.813115Z

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.

source=pdf_text observed=2026-08-06T17:17:32.089890Z digest=sha256:cff4b66a0082ec689f26d34f73af9680bae897c6159c7381836a949ba6b2cf67

Observation a81891e3-d1f1-44db-bc05-b4cd94728b57 · outbound

This paper cites Ge- omvsnet: Learning multi-view stereo with geometry percep- tion.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Ge- omvsnet: Learning multi-view stereo with geometry percep- tion

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:32.725965Z

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.

source=pdf_text observed=2026-08-06T17:17:32.170058Z digest=sha256:5e8e9cb5437d72741c5471e3b506b701e47d1ba51c889be259ae14d3b240f680

Observation 39a78809-1030-4812-8574-bb101ec3cf82 · outbound

This paper cites Sam2object: Consolidating view consistency via sam2 for zero-shot 3d instance segmentation.

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network Sam2object: Consolidating view consistency via sam2 for zero-shot 3d instance segmentation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:17:32.568714Z

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.

source=pdf_text observed=2026-08-06T17:17:32.245045Z digest=sha256:b36c3f4a8fd32bb2e92faa9a759a399d97b65e999f65e300f4197d47385b6715

Pith citing papers

No inbound Pith citation observations are available.