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Paper Citation Record · LEDGER

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images

As of 7 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 1 inbound Pith citation observation for arXiv:2506.07740.

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

pith.paper-citation-record.v1
2506.07740 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:33:54.116652Z

measured 95 of 95 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T11:29:19.914651Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

94 of 94 outbound references displayed

  • verified exact1
  • verified fuzzy74
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c3bdf08a-572b-45f6-81b2-1c5708cf3174 · outbound

This paper cites Object tracking in satellite videos based on a multiframe optical flow tracker,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Object tracking in satellite videos based on a multiframe optical flow tracker,

Reference 1

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Observation 82868004-9fa6-40b1-bc05-121807833087 · outbound

This paper cites Siamese-detr for generic multi- object tracking,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Siamese-detr for generic multi- object tracking,

Reference 2

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Observation 3e69676f-71b6-4f6f-b5ef-447819854700 · outbound

This paper cites Optical flow-based segmentation of moving objects for mobile robot navigation using pre-trained deep learning models,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Optical flow-based segmentation of moving objects for mobile robot navigation using pre-trained deep learning models,

Reference 3

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Observation b0b27218-4bcd-4f98-a6c3-bb0b618f902d · outbound

This paper cites Learning monocular 3d reconstruc- tion of articulated categories from motion,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Learning monocular 3d reconstruc- tion of articulated categories from motion,

Reference 4

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Observation 3e5febd8-56aa-49e2-a435-dcde46bd9c58 · outbound

This paper cites Flow- fusion: Dynamic dense rgb-d slam based on optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Flow- fusion: Dynamic dense rgb-d slam based on optical flow,

Reference 5

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Observation 00538166-cdd7-4ea7-957c-37bf2ebb3338 · outbound

This paper cites Improving monocular visual slam in dynamic environments: an optical-flow-based ap- proach,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Improving monocular visual slam in dynamic environments: an optical-flow-based ap- proach,

Reference 6

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Observation 3ce91636-3c75-446c-bea4-0b61ddd0d0d2 · outbound

This paper cites Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume,

Reference 7

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Source-reported events for the cited work

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Observation 23544dac-ef3f-45af-8225-2119c573d749 · outbound

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

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Raft: Recurrent all-pairs field transforms for optical flow,

Reference 8

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Observation e32b2e9c-d82c-404e-b545-37412a802b24 · outbound

This paper cites A lightweight optical flow cnn —revisiting data fidelity and regularization,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images A lightweight optical flow cnn —revisiting data fidelity and regularization,

Reference 9

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Observation 95e22663-80e9-4e14-afab-db589705c2e4 · outbound

This paper cites Motion detail preserving optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Motion detail preserving optical flow estimation,

Reference 10

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Observation 9af93bd0-925a-46d7-8b62-93a4cff77a50 · outbound

This paper cites Deep- flow: Large displacement optical flow with deep matching,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Deep- flow: Large displacement optical flow with deep matching,

Reference 11

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Observation 8b53ee18-b789-419e-afe4-90951d7cc191 · outbound

This paper cites Flownet: Learning op- tical flow with convolutional networks,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Flownet: Learning op- tical flow with convolutional networks,

Reference 12

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Observation 421eb532-bb89-4e12-b1b0-34b2a32a457c · outbound

This paper cites Flownet 2.0: Evolution of optical flow estimation with deep networks,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Flownet 2.0: Evolution of optical flow estimation with deep networks,

Reference 13

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Observation f5a85dd7-7e2d-45a1-8e72-760c797419a1 · outbound

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

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 14

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Observation 7de1a2df-1fae-4686-b390-fc0b5924e1a6 · outbound

This paper cites Object scene flow for autonomous vehicles,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Object scene flow for autonomous vehicles,

Reference 15

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Source-reported events for the cited work

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Observation d4c7ca85-cd94-4080-b8b9-c3ec62e23147 · outbound

This paper cites Dynamic shape capture via periodical- illumination optical flow estimation and multi-view photometric stereo,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Dynamic shape capture via periodical- illumination optical flow estimation and multi-view photometric stereo,

Reference 16

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Source-reported events for the cited work

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Observation a0a3aae3-5111-410e-ba57-3a12deebc625 · outbound

This paper cites Learning optical flow and scene flow with bidirectional camera-lidar fusion,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Learning optical flow and scene flow with bidirectional camera-lidar fusion,

Reference 17

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Observation a34c7f51-99e5-4a3e-a374-560ba7412017 · outbound

This paper cites Dense continuous- time optical flow from event cameras,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Dense continuous- time optical flow from event cameras,

Reference 18

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Observation 4b3aaf8d-5051-455e-a018-45aff1c623e9 · outbound

This paper cites How do neural networks estimate optical flow? a neuropsychology- inspired study,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images How do neural networks estimate optical flow? a neuropsychology- inspired study,

Reference 19

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Observation 5cb1d18d-974c-4acc-8c87-61db17e17c45 · outbound

This paper cites Instance segmen- tation in the dark,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Instance segmen- tation in the dark,

Reference 20

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Observation 8b6a2e90-4fee-49a9-b76a-7dc75b5a20ee · outbound

This paper cites Learning optical flow from still images,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Learning optical flow from still images,

Reference 21

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Source-reported events for the cited work

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Observation c9472c7f-0651-471d-a21d-6c83b6da1393 · outbound

This paper cites Realflow: Em-based realistic optical flow dataset generation from videos,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Realflow: Em-based realistic optical flow dataset generation from videos,

Reference 22

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Observation b1981d5e-2acb-4856-9d2f-44addc033cc0 · outbound

This paper cites Single-view view synthesis with mul- tiplane images,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Single-view view synthesis with mul- tiplane images,

Reference 23

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Observation b54959a2-c078-4a4d-a59b-856d02b0be8b · outbound

This paper cites Single-view view synthesis in the wild with learned adaptive multiplane images,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Single-view view synthesis in the wild with learned adaptive multiplane images,

Reference 24

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Source-reported events for the cited work

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Observation 8bb32027-9c03-4fa6-84f2-cf9ac9b6ca27 · outbound

This paper cites Virtual KITTI 2.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Virtual KITTI 2

Reference 26

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Observation 07965378-cfc1-4d2f-a217-bf89f1a82b0c · outbound

This paper cites Spring: A high-resolution high-detail dataset and benchmark for scene flow, optical flow and stereo,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Spring: A high-resolution high-detail dataset and benchmark for scene flow, optical flow and stereo,

Reference 27

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Source-reported events for the cited work

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Observation 6eba3e63-3ccc-4d7c-9195-09dbc8f5057c · outbound

This paper cites Stereo ground truth with error bars,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Stereo ground truth with error bars,

Reference 28

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Observation cf208f81-34d8-4d3e-a322-44bc4034e5df · outbound

This paper cites Multi-scale binocular stereo matching based on semantic association,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Multi-scale binocular stereo matching based on semantic association,

Reference 29

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Observation 3e26e391-5596-421d-9717-f0417580a978 · outbound

This paper cites Liteflownet: A lightweight convolutional neural network for optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Liteflownet: A lightweight convolutional neural network for optical flow estimation,

Reference 30

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Source-reported events for the cited work

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Observation 9adf627c-6785-423f-8c56-6d31ad13793e · outbound

This paper cites Iterative residual refinement for joint optical flow and occlusion estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Iterative residual refinement for joint optical flow and occlusion estimation,

Reference 31

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Observation 1b360999-0652-4031-8080-71b30ad82e02 · outbound

This paper cites Learning optical flow with adaptive graph reasoning,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Learning optical flow with adaptive graph reasoning,

Reference 32

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Observation 3c4718dd-4279-4320-8428-5745c7df1604 · outbound

This paper cites Transformer based pluralistic image completion with reduced information loss,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Transformer based pluralistic image completion with reduced information loss,

Reference 33

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Observation 64d28427-94a3-4442-a428-a7c7c07d92c9 · outbound

This paper cites Flowformer++: Masked cost volume autoencod- ing for pretraining optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Flowformer++: Masked cost volume autoencod- ing for pretraining optical flow estimation,

Reference 34

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Source-reported events for the cited work

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Observation 936bed64-45b9-4762-a8a1-80afc56a2a81 · outbound

This paper cites SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images SEA-RAFT: Simple, Efficient, Accurate RAFT for Optical Flow

Reference 35

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Observation 15fe043a-2471-43c8-9b48-f128e843b306 · outbound

This paper cites Physics-based noise mod- eling for extreme low-light photography,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Physics-based noise mod- eling for extreme low-light photography,

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0306ae51-9e5a-431a-920f-71a4f9516c3a · outbound

This paper cites Relation-guided adversarial learning for data- free knowledge transfer,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Relation-guided adversarial learning for data- free knowledge transfer,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.195212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:46.905773Z digest=sha256:0ae3f3ec5f9bbd4567aa6d524438f6b50ef4998283a7b293c9d153cebba44930

Observation 782a1eb3-6459-4a6a-8589-f3d3282753c5 · outbound

This paper cites Guided hyperspectral image denoising with realistic data,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Guided hyperspectral image denoising with realistic data,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.184349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:47.031999Z digest=sha256:4d51cd73e32ad60723a5fc40627c1dfce6b2911a6911fc2cee2751c63a19f66a

Observation 43780c11-2c92-4cae-a075-a313e8cd24b5 · outbound

This paper cites Low-light raw video denoising with a high-quality realistic motion dataset,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Low-light raw video denoising with a high-quality realistic motion dataset,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T05:33:47.139841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:33:47.139841Z digest=sha256:aeddb0a8fdd8e68ae9d4da43e9d557dade2875674e71bcf0aa1ba00b789f1250

Observation 92c54511-7e95-4f4d-8298-f1097bcba53c · outbound

This paper cites Eventhdr: From event to high-speed hdr videos and beyond,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Eventhdr: From event to high-speed hdr videos and beyond,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.167192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 42cf3658-6649-49f5-b768-fa3e4d5064cf · outbound

This paper cites A database and evaluation methodology for optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images A database and evaluation methodology for optical flow,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.157866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:47.369573Z digest=sha256:e33f080351731fbe8c45a2406d47f498432fe73d3228aed188f14293a7c271ec

Observation c6c3bc5e-8a59-4179-b744-e9839f8979ad · outbound

This paper cites Autoflow: Learning a better training set for optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Autoflow: Learning a better training set for optical flow,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.148009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:47.473053Z digest=sha256:0aca3217da6d255ce62c5d6a3263a67f688e3e1e3b1ba4226fdba5b625ada0de

Observation f5e3a5a5-aff8-4863-a091-fa4f3185a856 · outbound

This paper cites Mpi-flow: Learning realistic optical flow with multiplane images,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Mpi-flow: Learning realistic optical flow with multiplane images,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.137761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:47.653610Z digest=sha256:17d0622f8b3d6b3c2880d5258e0743c28e5255673fde17bf25a2b6164ca45f8c

Observation 72f78ee1-99de-41f9-ba5b-d5747856284c · outbound

This paper cites Neural Volumes: Learning Dynamic Renderable Volumes from Images.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Neural Volumes: Learning Dynamic Renderable Volumes from Images

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T05:33:47.803779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:33:47.803779Z digest=sha256:8ed54b58a913fbda4218247a6f6464ea0a2c3f1796f467c40dc90a145ed1a7a5

Observation d1a2fd31-cfc0-4150-9805-99ec4e573356 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Nerf: Representing scenes as neural radiance fields for view synthesis,

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T05:33:47.978932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:33:47.978932Z digest=sha256:b4755a979ed22ac55198aa95cdb52b0883adb8aad74b3bc0331cef8b8c64d22b

Observation ddd86d4a-3bb7-49c7-90cd-0e7ef88e9092 · outbound

This paper cites Hsi-guided intrinsic image decomposition for outdoor scenes,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Hsi-guided intrinsic image decomposition for outdoor scenes,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.120932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:48.126114Z digest=sha256:01d4dd5a82f7a44fadabe6f5f709e7adff5a9a95857dbe3383699cb3c946762e

Observation f97421c0-d45c-4085-8268-ba3f208e22cd · outbound

This paper cites Geometry-free view syn- thesis: Transformers and no 3d priors,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Geometry-free view syn- thesis: Transformers and no 3d priors,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.111746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:48.324798Z digest=sha256:f2c4f7e459a1656ad05f20fb93e1673ca7be0f91441d204d5d7e95750769a34e

Observation 33727bff-cc82-40ed-bb58-9e5a7d3c7eb2 · outbound

This paper cites Pixelsynth: Generating a 3d-consistent experience from a single image,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Pixelsynth: Generating a 3d-consistent experience from a single image,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.102189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:48.402406Z digest=sha256:395dd6087f9cc1a940276e7f332416608795dceb1b68e393fcd5c1adebc51dde

Observation f079012c-d5cf-4519-8802-5d66098e9ad2 · outbound

This paper cites Mine: Towards continuous depth mpi with nerf for novel view synthe- sis,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Mine: Towards continuous depth mpi with nerf for novel view synthe- sis,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.092135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:48.582784Z digest=sha256:ac6301006ff4568ecd23d9007af3732e946659f8cf1d567adfbd71785983bdd5

Observation 622178c1-25a9-416e-aea8-41ec620331b7 · outbound

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

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Depth anything: Unleashing the power of large-scale unlabeled data,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.082139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:48.715083Z digest=sha256:6bb9b45742c8d8640db3f857f7bc601888443e67bb75970037b1e414b1075af2

Observation f1e88481-2048-4d7f-a8f1-d5545d4592b4 · outbound

This paper cites Multiple view geometry,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Multiple view geometry,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.061914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:48.988307Z digest=sha256:46d786ba584e3aebc8b1bceeb4f7ab9bbd9db28eb3a88e56ee6c85d50705341b

Observation 419e3ad1-f171-45c0-990b-4cc76ee52d2d · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images High-resolution image synthesis with latent diffusion models,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.052692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:49.104227Z digest=sha256:59074735cd9e0f6c2ce528e63d0d7a663b7275e628c7515400e1d373fe554107

Observation e9ad5295-813c-4859-813d-0fbe7d03074c · outbound

This paper cites A naturalistic open source movie for optical flow evaluation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images A naturalistic open source movie for optical flow evaluation,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.297396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:49.308462Z digest=sha256:690dec90a05050c706e223b6e05e26394fe1612a9cbf953dd982a762e0cd7c39

Observation 7ba530a6-19f7-459c-be5d-1d67735d97fd · outbound

This paper cites Bdd100k: A diverse driving dataset for hetero- geneous multitask learning,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Bdd100k: A diverse driving dataset for hetero- geneous multitask learning,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.042607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:49.462340Z digest=sha256:8ea71ffe7dd6c5693d968fd4113393e959603f8c644456aa9e1449c2abb97a1f

Observation e623816d-a920-41be-847b-ffe9b232227a · outbound

This paper cites Microsoft coco: Common objects in context,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Microsoft coco: Common objects in context,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.032380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:49.688087Z digest=sha256:68ec3a1381a0c35f5cdc8d01e0505e98ba9f3b02bd340af06a3d5d17df47519f

Observation 8743a2ca-820c-4354-b4a8-4539ac8029b0 · outbound

This paper cites Google landmarks dataset v2-a large-scale benchmark for instance-level recognition and retrieval,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Google landmarks dataset v2-a large-scale benchmark for instance-level recognition and retrieval,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.022481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:49.835916Z digest=sha256:17561a9d4c3a13703f4ee56f759d2e7fa38680a79e9372be270e5cc17b37a91b

Observation a47ee091-eea3-46a9-b9b9-e232132da8da · outbound

This paper cites nuscenes: A mul- timodal dataset for autonomous driving,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images nuscenes: A mul- timodal dataset for autonomous driving,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.012806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:49.989891Z digest=sha256:854c733ea56d4200c1b2a93a2210d28ef17e25c9aa358db1311cd0080141d360

Observation 42dd22a2-1bfa-4ddc-b6cc-3115f00b8832 · outbound

This paper cites Sun rgb-d: A rgb-d scene understanding benchmark suite,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Sun rgb-d: A rgb-d scene understanding benchmark suite,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.002526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.094233Z digest=sha256:29ec65ff279756eb66cdfbaff6542ae6f03e63ddf5a753546dcd0fe4aac41fc9

Observation 7b9618d3-5647-423b-a12a-c6f64d2ef2ef · outbound

This paper cites Vision meets robotics: The kitti dataset,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Vision meets robotics: The kitti dataset,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.991648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.212505Z digest=sha256:42e06c3029a31830363293a5b2af9c683e9b0d0936b600a85b5703c38c602628

Observation bf68993e-90ce-41a5-bc96-6d8440f6412b · outbound

This paper cites Indoor segmen- tation and support inference from rgbd images,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Indoor segmen- tation and support inference from rgbd images,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.981667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.382751Z digest=sha256:48ffd611956facbab72ea991f50037aa9a42a1dc6a8a1afe7efd99c36fb20c56

Observation 15fb85ce-5e1a-4045-b558-a61ae6f30185 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images The cityscapes dataset for semantic urban scene understanding,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.971446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.533970Z digest=sha256:60c0f3f4dc9af082e16fb9440ef5d7ba985e49b0bcecc366584266cecb6696e8

Observation 700ce5c0-b096-47f0-8f8a-206b8aada1bc · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images A benchmark dataset and evaluation methodology for video object segmentation,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.960802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.646026Z digest=sha256:e6273ca63e5736fa83be2dbe31c0488e95afccc960404bad29d667da297e534a

Observation 0820dc34-de6d-4998-9325-3268838c6dc7 · outbound

This paper cites Masked-attention mask transformer for universal image segmen- tation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Masked-attention mask transformer for universal image segmen- tation,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:56.072000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.787271Z digest=sha256:06c765980dc6d63cfc4c90274545ddddf01fec5fbc1fbd8a84631f9b7d00fd2b

Observation 5dcefa69-e7a2-4f3a-a9ed-ef8fe1725c05 · outbound

This paper cites Learning to estimate hidden motions with global motion aggregation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Learning to estimate hidden motions with global motion aggregation,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.950209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:50.951449Z digest=sha256:e3f115d55726960e42d4edadb66ed5d6bd0e7b5a8aa9e035ec05e512a0dceff8

Observation dd0c4256-18a6-4d88-9d56-b2397ee28a87 · outbound

This paper cites Skflow: Learning optical flow with super kernels,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Skflow: Learning optical flow with super kernels,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.938898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.079064Z digest=sha256:85d1f8f2fcfa93f53fdfa13c9f4b4bfcd8499c2571f3a3c0ba248a5f3719012f

Observation f387b999-bc6b-4db4-81f9-2ebbd0590726 · outbound

This paper cites Flowformer: A transformer architecture for optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Flowformer: A transformer architecture for optical flow,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.928588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.149902Z digest=sha256:3be02690130bd09aa802436d795549c790e70ce21d2210df222dc8d949a78c0b

Observation 8a1c3565-4d88-4ad6-905f-88c378919651 · outbound

This paper cites Dip: Deep inverse patchmatch for high-resolution optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Dip: Deep inverse patchmatch for high-resolution optical flow,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.918740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.304602Z digest=sha256:13de869492ec84d4afb72fbe7933e93c26a450c85aaccc6a81d07d6c749a7a78

Observation d78afe54-6ddb-4dc3-af08-7eea26a681c9 · outbound

This paper cites Explicit motion disentangling for efficient optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Explicit motion disentangling for efficient optical flow estimation,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.908195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.375771Z digest=sha256:7565b47cf2d069d83ee79a67b0876f9b2ed9883a55b0661e14ad2e85927948a9

Observation 93d6432d-790d-4743-81c7-923eeb0d38fc · outbound

This paper cites Craft: Cross-attentional flow transformer for robust optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Craft: Cross-attentional flow transformer for robust optical flow,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.898118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.500976Z digest=sha256:d004949d42f74f674eff5d95803ba409d4e4448a84e1bfbf421cf61fc60ce648

Observation f3247eaf-ddbb-469c-81e9-5974be0dc649 · outbound

This paper cites Recurrent partial kernel network for efficient optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Recurrent partial kernel network for efficient optical flow estimation,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.888763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.609453Z digest=sha256:a61a9183b0b5e6019d557a7d2b71696d975bb7227d73f14efea7554bf9cb1765

Observation 14a1dfe0-7b07-40fd-b1a7-ac52b633c07b · outbound

This paper cites Global matching with overlapping attention for optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Global matching with overlapping attention for optical flow estimation,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.879069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.773168Z digest=sha256:e4475841bb40b0c209c9124ac58c9824cd5184212d89602625aef880640ceb66

Observation 7e718602-5e92-48c2-bb5c-39c0ac2d6b87 · outbound

This paper cites Gmflow: Learning optical flow via global matching,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Gmflow: Learning optical flow via global matching,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.869031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:51.859870Z digest=sha256:8fcd532fcf646ba95548a1a7d4d6dd7ce952179753dc230b09afe1c5995405be

Observation 80aa33e3-e402-4400-a858-582e2bbd1fd7 · outbound

This paper cites Unifying flow, stereo and depth estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Unifying flow, stereo and depth estimation,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.859812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.011763Z digest=sha256:fecfdfed56cdd87767c87a9975aba11960d2d43064b87191f5b93d469da32def

Observation 5cfb6ed7-3a4d-4412-a99d-10442bed06c0 · outbound

This paper cites Youtube-vos: Sequence-to-sequence video object segmentation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Youtube-vos: Sequence-to-sequence video object segmentation,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.849781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.158052Z digest=sha256:2741dfe2ff60617608fcd611db63bd8d1109f1ed8c063f6a7c8ffad50eead5c5

Observation 57a3ddf2-c4e5-4caf-923e-8b356fbcdbbb · outbound

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

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Tartanair: A dataset to push the limits of visual slam,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.838921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.271709Z digest=sha256:004bc8ab679df3ac283a0058bd788d6921987d45869a73abdef803cefe8f0299

Observation 7916db84-4f05-4828-966d-fd93299553b7 · outbound

This paper cites Unflow: Unsupervised learning of optical flow with a bidirectional census loss,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Unflow: Unsupervised learning of optical flow with a bidirectional census loss,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.828190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.423433Z digest=sha256:80c8dfa58fa2677d07e85ce054136ea19bb3d711f51e0dda691da4ed3ed7f20e

Observation a65bd20f-cfa7-4637-bb12-45be9d3a30c8 · outbound

This paper cites Ddflow: Learning optical flow with unlabeled data distillation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Ddflow: Learning optical flow with unlabeled data distillation,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.817482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.580153Z digest=sha256:17fe7c20f8f870e008d2c9f83b60dad9bd6a349e1149dd6dedb5ae3fc3a30006

Observation c41cd526-c688-470e-8f07-f4455432f025 · outbound

This paper cites Selflow: Self-supervised learning of optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Selflow: Self-supervised learning of optical flow,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.805614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.644526Z digest=sha256:74d53e70595c0934fe1be2feb1801dcc9621e8823d7ac99fbe8f1b97fa7d6fb3

Observation e8de33d6-29e3-4f86-8a2a-b7cd9900dff1 · outbound

This paper cites Unsupervised learning of op- tical flow with deep feature similarity,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Unsupervised learning of op- tical flow with deep feature similarity,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.794404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.790929Z digest=sha256:caa0dbb01d5f7be4278e953ce470eceb524d1f51b6d36ffbad1a3ae0de052ad5

Observation 9bc0203f-2cf6-44cb-8e5d-d134c2d06a07 · outbound

This paper cites What matters in unsupervised optical flow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images What matters in unsupervised optical flow,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.784720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:52.884229Z digest=sha256:9392f75cb918bebda659f15d15f6237da91ee7a4d2cc5c72f975cb6be2978105

Observation 43438b09-0d84-4181-b304-6542a8be7408 · outbound

This paper cites Upflow: Upsampling pyramid for unsupervised optical flow learning,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Upflow: Upsampling pyramid for unsupervised optical flow learning,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.774589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.032639Z digest=sha256:39d697f77cea9e1f1659cd5ed510e5d4dddba7421f08d09606974346a135f930

Observation b7fe14b4-f1ee-4a19-996e-e59fae5e8446 · outbound

This paper cites Learning by analogy: Reliable supervision from transformations for unsupervised optical flow estimation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Learning by analogy: Reliable supervision from transformations for unsupervised optical flow estimation,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.763129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.186619Z digest=sha256:556be239b9b91c136b34698da0292b5db7dcd3964f56fbfcf7e0efd3f4b35c49

Observation 4d863d27-1304-4962-9c36-df1924585023 · outbound

This paper cites Semarflow: Injecting se- mantics into unsupervised optical flow estimation for autonomous driving,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Semarflow: Injecting se- mantics into unsupervised optical flow estimation for autonomous driving,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.752252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.263042Z digest=sha256:cc3bd4a77254a4f7ab07eeb05996f07ccd273e83f3067d87c740878b1cba7e22

Observation d73b4c22-cd0e-429f-9d14-4806871c5dab · outbound

This paper cites Semi-supervised learning of optical flow by flow supervisor,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Semi-supervised learning of optical flow by flow supervisor,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.741471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.339809Z digest=sha256:274ee665864feca739b271535e28bef7893e6ac68e9827bd5aedb81006627bae

Observation bc1fffdb-3ef0-4f57-aa7e-1483af0adabb · outbound

This paper cites UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model

Reference 86

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:33:54.279064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.387897Z digest=sha256:c57a96161e90bb71fdf24f34878f6bd963a8b9e9dde849bcc7d2286e033e33b1

Observation ccef2381-ce3c-47e7-ac70-5e3e5736d61d · outbound

This paper cites Self-supervised autoflow,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Self-supervised autoflow,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.730340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.454164Z digest=sha256:f5f74c61e0087eb2d5f8292edb3f46a2286ee62d54d3927b0ab8e15d409e9c0f

Observation 27d4ba9b-2916-40c4-8215-299f3d53917e · outbound

This paper cites Smurf: Self-teaching multi-frame unsupervised raft with full- image warping,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Smurf: Self-teaching multi-frame unsupervised raft with full- image warping,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.718729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.563144Z digest=sha256:62b2c99f0ab73c2ec9acea915224f980aca0d9efc4004a681fce892c47b01442

Observation 7cce5367-0b02-478c-9477-5c90b46b2abc · outbound

This paper cites Tap-vid: A benchmark for tracking any point in a video,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Tap-vid: A benchmark for tracking any point in a video,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.707503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.646701Z digest=sha256:fe22f4a3ce0a559e2dfd474f4c7fb866cb302b9e1b50f90b7f50d54bf5f37385

Observation 19b664d8-f2f0-4bae-ab83-37d941a9a6a0 · outbound

This paper cites Propainter: Improving propagation and transformer for video inpainting,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Propainter: Improving propagation and transformer for video inpainting,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.681180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.732240Z digest=sha256:afde3ea95f14d4a137e9e1e85654bdc1a661d76a3c4acd6ff43b18d274260f07

Observation 3ca2286e-2d39-4646-9b27-358758b68c9c · outbound

This paper cites Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.525897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.798259Z digest=sha256:6880dd5555472a732dc6dab81d69c81e93c40a00ce57bc87c9fbb04ea28f0529

Observation 9ca9e946-c566-432d-8ee9-7722cd8daad5 · outbound

This paper cites Treating motion as option to reduce motion dependency in unsupervised video object segmentation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Treating motion as option to reduce motion dependency in unsupervised video object segmentation,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.281230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.849145Z digest=sha256:1c2c654a611671edceb6171f4aac5b6f2847805d027c4aa0b82ad74ee77516fd

Observation 20e78951-057f-4431-8bbf-da9586d445bb · outbound

This paper cites Dynamic view syn- thesis from dynamic monocular video,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Dynamic view syn- thesis from dynamic monocular video,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:55.024955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.919337Z digest=sha256:6528cc08aff50feb6a3148e35f1f3ff97439547ce5c28063312eaa5a728b8f3d

Observation 7593c6e6-04ec-49aa-bf75-52a0299e5d92 · outbound

This paper cites Neural scene flow fields for space-time view synthesis of dynamic scenes,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Neural scene flow fields for space-time view synthesis of dynamic scenes,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:54.788835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:53.983297Z digest=sha256:5ff3e78b7aab3e133153d791b8f162f8d175e81866d918b2638252ca482985b7

Observation c448eadf-921c-460f-a7a6-b2ba378f3ac0 · outbound

This paper cites FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:54.578993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:54.041501Z digest=sha256:c041793fa7dcaddea469138b4e79e77aa8debc5b7218aa01c9e1dfcc30d3238f

Observation b2b6f601-c0ef-4ae3-bec2-971060bcad6c · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation,.

Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:33:54.429284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:33:54.116652Z digest=sha256:35d2f5f2f7c37dd576bdc2bb113329c0fee26a867adae28dbf74c3624833e274

Pith citing papers

Observation 8931c9b9-9e23-401c-ad98-32b3411c90b1 · inbound

On the Real-World Generalisability of Optical Flow Models cites this paper.

On the Real-World Generalisability of Optical Flow Models Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-14T11:29:19.914651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T11:29:19.914651Z digest=sha256:1e897651a6bde0de028034dae19656d55b4f3aeaf107edef155004a574d87907