Paper Citation Record · LEDGER

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM

As of 5 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:1907.11628.

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

pith.paper-citation-record.v1
1907.11628 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T15:47:47.462615Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

24 of 24 outbound references displayed

verified exact2
verified fuzzy21
unresolved0
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ab53f8e4-1f69-44a6-9487-146b759a9f7b · outbound

This paper cites coarse-to- ﬁne.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM coarse-to- ﬁne

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.751340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ef26cecc-eaf4-4618-9111-b4aba6cc8e4b · outbound

This paper cites Correlation.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Correlation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.799944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6f9a15fe-63ef-466f-8fab-6ce903157d63 · outbound

This paper cites W” denotes “inverse warp.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM W” denotes “inverse warp

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.803577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 74886fa7-f987-46f9-ae41-21e2d10cc76c · outbound

This paper cites couple connection.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM couple connection

Reference 4

Resolution: malformed identifier; raw_fallback, observed 2026-05-24T15:49:40.811239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1cee4d0f-b219-4333-a705-90a9461bb9fc · outbound

This paper cites By utilizing reconstruction constraint as supervision, our framework is able to efﬁciently learn optical ﬂow on real-world videos without groundtruth.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM By utilizing reconstruction constraint as supervision, our framework is able to efﬁciently learn optical ﬂow on real-world videos without groundtruth

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.807458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3edc6f8d-eab9-4a87-80cc-a3eaee9458b6 · outbound

This paper cites A duality based ap- proach for realtime tv-l1 optical ﬂow.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM A duality based ap- proach for realtime tv-l1 optical ﬂow

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.815109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 38c7718b-4eab-4d12-af83-d51e4425d5ac · outbound

This paper cites Determining optical ﬂow.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Determining optical ﬂow

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.822657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d1ca9f44-9137-4cd9-b5d4-1b155f81d9c3 · outbound

This paper cites Flownet: Learning optical ﬂow with convo- lutional networks.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Flownet: Learning optical ﬂow with convo- lutional networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.834819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d7ee13ba-1667-4d72-8f10-24a852f66ef6 · outbound

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

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Flownet 2.0: Evolution of optical ﬂow estimation with deep networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.796516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e5aeeee4-d567-4222-8293-18694fe80b92 · outbound

This paper cites PWC-Net: CNNs for optical ﬂow using pyramid, warping, and cost volume.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM PWC-Net: CNNs for optical ﬂow using pyramid, warping, and cost volume

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.784431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 720d88f2-0744-4156-a7e9-ab1b917aa70b · outbound

This paper cites Back to basics: Unsupervised learning of optical ﬂow via bright- ness constancy and motion smoothness.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Back to basics: Unsupervised learning of optical ﬂow via bright- ness constancy and motion smoothness

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.788274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 52b66b38-42c1-4c53-9a6c-cca46224de8e · outbound

This paper cites Hidden Two-Stream Convolutional Networks for Action Recognition.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Hidden Two-Stream Convolutional Networks for Action Recognition

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-24T15:49:39.766753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5c43d4a7-1e12-4736-be07-ffa310f416b1 · outbound

This paper cites The robust estimation of multiple motions: Parametric and piecewise-smooth ﬂow ﬁelds.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM The robust estimation of multiple motions: Parametric and piecewise-smooth ﬂow ﬁelds

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.819176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 090047a9-c1eb-442e-b43a-3d4f6853268d · outbound

This paper cites U-net: Convo- lutional networks for biomedical image segmentation.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM U-net: Convo- lutional networks for biomedical image segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.780341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b62a8d48-0656-4a2d-9c36-55ed405e4940 · outbound

This paper cites Optical ﬂow estimation using a spatial pyramid network.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Optical ﬂow estimation using a spatial pyramid network

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.830811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2f096dbe-f468-485a-828e-da46160b478a · outbound

This paper cites Deep resid- ual learning for image recognition.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Deep resid- ual learning for image recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.838659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2836725a-c227-4feb-b57a-9114dcfa0be1 · outbound

This paper cites Spatial pyra- mid pooling in deep convolutional networks for visual recognition.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Spatial pyra- mid pooling in deep convolutional networks for visual recognition

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.792996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b46f180c-babf-4b07-843c-0f05cd8af194 · outbound

This paper cites Spatial transformer networks.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Spatial transformer networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.772264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bc3beb4b-fc76-4e6d-ac88-c1124a9828df · outbound

This paper cites Image quality assessment: from error vis- ibility to structural similarity.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Image quality assessment: from error vis- ibility to structural similarity

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.768738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d246b6d5-0e77-49cb-a5c4-5708138dca11 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-24T15:49:39.772681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bd9c3385-7f45-4c78-aa04-dc0c7d1973f6 · outbound

This paper cites Hmdb: a large video database for human mo- tion recognition.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Hmdb: a large video database for human mo- tion recognition

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.760618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 01c5ca42-27b2-415c-91a2-4903242b80e5 · outbound

This paper cites A naturalistic open source movie for optical ﬂow evalua- tion.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM A naturalistic open source movie for optical ﬂow evalua- tion

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.826848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9ddf55c7-1a22-4204-98e7-bea23e0eb6d0 · outbound

This paper cites Fast optical ﬂow using dense inverse search.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Fast optical ﬂow using dense inverse search

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.764964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 34517416-a207-4a88-aada-63c5acefe074 · outbound

This paper cites Deepﬂow: Large displacement optical ﬂow with deep matching.

Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM Deepﬂow: Large displacement optical ﬂow with deep matching

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T15:49:40.755923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

No inbound Pith citation observations are available.