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Paper Citation Record · LEDGER

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching

As of 17 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.13674.

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

pith.paper-citation-record.v1
2607.13674 v1

Coverage vector

measured 37 of 37 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-02T04:33:08.524750Z

measured 37 of 37 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

37 of 37 outbound references displayed

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Outbound references

Observation 8686fccd-ffce-4756-afbd-f3eab5fe1409 · outbound

This paper cites Bridgedepth: Unifying monocular and stereo depth estimation.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Bridgedepth: Unifying monocular and stereo depth estimation

Reference 1

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Observation 6f82850d-4176-4331-ad85-3ec2f65c37a9 · outbound

This paper cites Waft: Warping-alone field transforms for opti- cal flow.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Waft: Warping-alone field transforms for opti- cal flow

Reference 2

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Observation 1a6b89eb-3b09-43d0-8725-6b8d085dd616 · outbound

This paper cites Fast-foundationstereo: Real-time zero-shot stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Fast-foundationstereo: Real-time zero-shot stereo matching

Reference 3

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Observation 7ea299f2-8c5e-4e0f-a391-946e7738235b · outbound

This paper cites Lite any stereo: Efficient zero-shot stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Lite any stereo: Efficient zero-shot stereo matching

Reference 4

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Observation 17fa0d25-eb96-48ca-891e-5bf6291d7f7f · outbound

This paper cites Waft-stereo: Warping-alone field transforms for stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Waft-stereo: Warping-alone field transforms for stereo matching

Reference 5

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source=pdf_text observed=2026-08-02T04:33:06.233470Z digest=sha256:0e5eb252f8c5730610df98249775132ac2f6b969dd82ae9147c94891b93b5699

Observation 9010bc69-d35c-47e8-92dd-b22ad4cf3e3a · outbound

This paper cites Cleardepth: En- hanced stereo perception of transparent objects for robotic manipulation.arXiv preprint arXiv:2409.08926, 2024.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Cleardepth: En- hanced stereo perception of transparent objects for robotic manipulation.arXiv preprint arXiv:2409.08926, 2024

Reference 6

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Observation 65ff8794-47b8-4335-ac09-627e6fab24f1 · outbound

This paper cites Correlate-and- excite: Real-time stereo matching via guided cost volume excitation.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Correlate-and- excite: Real-time stereo matching via guided cost volume excitation

Reference 7

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Observation 013305b3-102a-4084-9ebf-59df46d88c18 · outbound

This paper cites In- stereo2k: A large real dataset for stereo matching in indoor scenes.SCIS, 2020.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching In- stereo2k: A large real dataset for stereo matching in indoor scenes.SCIS, 2020

Reference 8

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Observation 5da87c0f-1db4-4298-b2fc-16f745c7a993 · outbound

This paper cites Vir- tual kitti 2.arXiv, 2020.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Vir- tual kitti 2.arXiv, 2020

Reference 9

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Observation 6286b96b-1d6c-4c9e-9ffe-14edaefb903f · outbound

This paper cites Monster++: A unified geometric foun- dation model for multi-view depth estimation via harness- ing monodepth priors.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Monster++: A unified geometric foun- dation model for multi-view depth estimation via harness- ing monodepth priors

Reference 10

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Observation 6f52f89b-fe95-44b3-862d-1a4beaaeec97 · outbound

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

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 11

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Observation c3edf885-102b-4818-a852-a7fc3a399aff · outbound

This paper cites Light- stereo: Channel boost is all you need for efficient stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Light- stereo: Channel boost is all you need for efficient stereo matching

Reference 12

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source=pdf_text observed=2026-08-02T04:33:06.682840Z digest=sha256:5fc918f19e5555fc19e5eb59d4253fec8ad100f8c1ec2403f75275b57d503234

Observation 54fda66d-a2a9-43b8-a35f-8258af680754 · outbound

This paper cites Stereonet: Guided hierarchical refinement for real-time edge-aware depth prediction.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Stereonet: Guided hierarchical refinement for real-time edge-aware depth prediction

Reference 13

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source=pdf_text observed=2026-08-02T04:33:06.735796Z digest=sha256:6457d9e0c0ed646b2e85a528da2da4c18cd8260cb545b0f91b9a329fbfda745c

Observation 865a5ab7-3e92-45e2-a834-f1b13e14402e · outbound

This paper cites Practical stereo matching via cascaded recurrent net- work with adaptive correlation.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Practical stereo matching via cascaded recurrent net- work with adaptive correlation

Reference 14

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source=pdf_text observed=2026-08-02T04:33:06.794801Z digest=sha256:5d52ad93bba5a38c0e03334d4f05fca4d9f176c035bcbfeb52046044b370163a

Observation 7275bfdf-d489-4727-9ce1-26bb7e9c4118 · outbound

This paper cites Raft-stereo: Multilevel recurrent field transforms for stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Raft-stereo: Multilevel recurrent field transforms for stereo matching

Reference 15

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source=pdf_text observed=2026-08-02T04:33:06.844880Z digest=sha256:9745dc13059411d6e69187d6da1db94c8046a29e20a081cec1c04ffd6703b68c

Observation c3cb7a07-f153-43ec-a123-90cabf5750a6 · outbound

This paper cites Decoupled weight decay regularization.Int.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Decoupled weight decay regularization.Int

Reference 16

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Observation 8efd87d2-16d7-420b-ba18-fdbce4a36017 · outbound

This paper cites A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 17

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source=pdf_text observed=2026-08-02T04:33:06.930587Z digest=sha256:822f0214f8f989cb8bad4b092d49a739b24a85e1335ce55ad28f98e808682cad

Observation 1574f3f4-2df0-445f-9247-fa59b9e5c1a4 · outbound

This paper cites Object scene flow for autonomous vehicles.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Object scene flow for autonomous vehicles

Reference 18

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source=pdf_text observed=2026-08-02T04:33:06.990141Z digest=sha256:27246287ea6f817d1741680d1389da845a40466a7fd6c45f4ca31ca8e9812721

Observation 8fc5ed60-1e6f-4ea6-9fe4-d2ccedc27e29 · outbound

This paper cites Booster: A benchmark for depth from images of specular and transpar- ent surfaces.IEEE Trans.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Booster: A benchmark for depth from images of specular and transpar- ent surfaces.IEEE Trans

Reference 19

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source=pdf_text observed=2026-08-02T04:33:07.084962Z digest=sha256:a327e5f626c0b9835a5cd0e39f885ef35fea6d2c3fdc9cf500c874122a2d87b3

Observation 39aaac6e-320a-43d6-9ffc-99cd0abff0a5 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 20

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Observation e6295ecb-d8cd-4702-b2de-7ca325295287 · outbound

This paper cites High-resolution stereo datasets with subpixel-accurate ground truth.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching High-resolution stereo datasets with subpixel-accurate ground truth

Reference 21

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Observation 1fdac3cf-cc56-4725-ab72-b1e8f4d3ebbb · outbound

This paper cites Sch¨onberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and An- dreas Geiger.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Sch¨onberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and An- dreas Geiger

Reference 22

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source=pdf_text observed=2026-08-02T04:33:07.374206Z digest=sha256:42411ca7369552aa0a5b1ddd95c4d8386e0d53ec5da7e612881b4d533ae1e8ad

Observation 0613777a-30cf-4a9d-b59e-3635021d5d8b · outbound

This paper cites Mobilestereonet: Towards lightweight deep net- works for stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Mobilestereonet: Towards lightweight deep net- works for stereo matching

Reference 23

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Observation abee89e0-7c77-4ca8-a1a1-7999020a02ca · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Raft: Recurrent all-pairs field transforms for optical flow

Reference 24

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Observation 51c09b39-c58b-4619-944f-598c0c5983e6 · outbound

This paper cites Smd-nets: Stereo mixture density networks.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Smd-nets: Stereo mixture density networks

Reference 25

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source=pdf_text observed=2026-08-02T04:33:07.597693Z digest=sha256:f92fa31e9cd503b3b221bff5a66f8b53856048c6b56c4e593092ba3a23760a0b

Observation 8bbd68f3-3c9e-463c-a0d6-3875f695a90a · outbound

This paper cites Falling things: A synthetic dataset for 3d object detection and pose estimation.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Falling things: A synthetic dataset for 3d object detection and pose estimation

Reference 26

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Observation 6cb1297f-82e7-4b3a-962b-3ca3737f961e · outbound

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

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching IRS: A large naturalistic indoor robotics stereo dataset to train deep models for dis- parity and surface normal estimation

Reference 27

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Observation e6248744-20b1-4806-b4fd-86e7efd33d9f · outbound

This paper cites Tartanair: A dataset to push the limits of visual slam.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Tartanair: A dataset to push the limits of visual slam

Reference 28

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Observation 5dfb24e9-d3e7-447b-abe0-891ba490054e · outbound

This paper cites Selective-stereo: Adaptive frequency information selection for stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Selective-stereo: Adaptive frequency information selection for stereo matching

Reference 29

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Observation 7e435c97-898d-467d-99b3-4ae79e0bf4d2 · outbound

This paper cites Foundationstereo: Zero-shot stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Foundationstereo: Zero-shot stereo matching

Reference 30

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Observation 543dc327-9f27-4beb-bf45-92a85bf4fc94 · outbound

This paper cites Bilateral grid learning for stereo matching networks.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Bilateral grid learning for stereo matching networks

Reference 31

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source=pdf_text observed=2026-08-02T04:33:08.030246Z digest=sha256:0b64a3c566b6b897908fd9b67a58fd425898e5a6bb809c799518ce33d756c20a

Observation 049d8d44-a892-4753-ac73-26a051aebb2a · outbound

This paper cites Iterative geometry encoding volume for stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Iterative geometry encoding volume for stereo matching

Reference 32

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Observation 3880a8ca-b0bf-4f5c-a658-461a8997f04f · outbound

This paper cites Accurate and efficient stereo matching via attention concatenation volume.IEEE Transactions on Pattern Anal- ysis and Machine Intelligence, 2023.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Accurate and efficient stereo matching via attention concatenation volume.IEEE Transactions on Pattern Anal- ysis and Machine Intelligence, 2023

Reference 33

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Observation b5ecbe6d-a070-4124-8eb4-6ed74246efa2 · outbound

This paper cites Igev++: Iterative multi-range geometry en- coding volumes for stereo matching.IEEE Trans.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Igev++: Iterative multi-range geometry en- coding volumes for stereo matching.IEEE Trans

Reference 34

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Observation 3a63aad7-7796-4b36-8b1c-dabf218b6a93 · outbound

This paper cites Aanet: Adaptive aggrega- tion network for efficient stereo matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Aanet: Adaptive aggrega- tion network for efficient stereo matching

Reference 35

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Observation b1fc8025-0a5a-4043-9841-53ba141788c7 · outbound

This paper cites MatchAttention: Embedding Explicit Matching Constraints into Attention for Efficient Stereo Matching.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching MatchAttention: Embedding Explicit Matching Constraints into Attention for Efficient Stereo Matching

Reference 36

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This paper cites Depth any- thing v2.

WAVE-Stereo: Warp-Aligned Volume Encoding for Stereo Matching Depth any- thing v2

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