Pith. sign in

Paper Citation Record · LEDGER

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices

As of 12 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2412.13273.

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

pith.paper-citation-record.v1
2412.13273 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:22:31.205522Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

72 of 72 outbound references displayed

  • verified exact1
  • verified fuzzy58
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ee60bfca-3522-4722-a8ff-aff9f0829421 · outbound

This paper cites tensorflow lite.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices tensorflow lite

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:32.044818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.929987Z digest=sha256:738e872814a1ff92e330c6e48540b6f96575282b7c7152c80a866c40389d59e1

Observation 58337263-fdb1-4adb-b121-d6024310f07b · outbound

This paper cites Mur- ray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete War- den, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Mur- ray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete War- den, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:32.032863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.934452Z digest=sha256:e5771e118db7987df6ad5ec0f4930eaa089177681375fc4d922c9fffcce7c43e

Observation 915ad026-72b1-4c57-ae1f-b3d94a1a4119 · outbound

This paper cites Video stabilization us- ing raft-based optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Video stabilization us- ing raft-based optical flow

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:32.020678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.938456Z digest=sha256:b41759c93235cc54e1a7dd0b6bfe96cf4f6170b07e2c32939055bb9c0d6ac8c8

Observation 98692e75-baa1-4153-b5ae-b34346542536 · outbound

This paper cites Large displacement optical flow: descriptor matching in variational motion estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Large displacement optical flow: descriptor matching in variational motion estimation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:32.008225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.942359Z digest=sha256:41856c6c1f91e8b64054e46e852a7ebc52791292d94e16f67bfb49b670df0d90

Observation f3985bf6-e032-4063-a33e-47b946d7e415 · outbound

This paper cites Mpi-sintel optical flow benchmark: Supplemental material.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Mpi-sintel optical flow benchmark: Supplemental material

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.995453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.946740Z digest=sha256:2853024395263550c7eb5fc11dec71f1420f42399a99f93775dfdb93a60ed4a3

Observation ec8efe61-31fc-475d-901e-c011cf186cba · outbound

This paper cites Basicvsr: The search for essential compo- nents in video super-resolution and beyond.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Basicvsr: The search for essential compo- nents in video super-resolution and beyond

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.984118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.950638Z digest=sha256:61082e3d4b85e2f7c112100ccd7f0231a360a94f60513c4d7f15aab165f3055d

Observation 196e8d95-8686-4123-932a-0f77441cac98 · outbound

This paper cites Improved optical flow for gesture-based human-robot interaction.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Improved optical flow for gesture-based human-robot interaction

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.972386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.954743Z digest=sha256:78abcb3714e45540f47c9378b59c276d2b816cc45b89d40da6f2168c99c0a535

Observation 123aac90-f0b5-43f7-964e-207fcc25fd32 · outbound

This paper cites Learning on-road visual control for self-driving vehicles with auxiliary tasks.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Learning on-road visual control for self-driving vehicles with auxiliary tasks

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.960498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.958373Z digest=sha256:0bd767b173b96255546199020647910365dfbef3c9a340344cd8d0b575d87a42

Observation 4af63246-d73a-42ac-b0ae-5fe7a720ec73 · outbound

This paper cites Mfcflow: A motion feature compensated multi-frame recurrent network for optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Mfcflow: A motion feature compensated multi-frame recurrent network for optical flow estimation

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.948003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.961925Z digest=sha256:b2005ab14f89cfc306a8df7d07f107c054c65516993b337dddafb6f8e9100558

Observation b7e5fd1d-b1ce-46ce-acf2-4f6e95e06c4f · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Imagenet: A large-scale hierarchical image database

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:30.965629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:30.965629Z digest=sha256:0e56d5cf45acb9950124537d51294e2ea7029881b62ed4b85c908a884229a0ec

Observation aff10979-0800-475a-a672-b07f9e767f8b · outbound

This paper cites Flownet: Learning optical flow with convolutional networks.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Flownet: Learning optical flow with convolutional networks

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.929709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.969444Z digest=sha256:1400cfccb9104217ba900611a066a734ee7c3709b3a27fb285ab13f47aae6ff9

Observation a6e44f2e-99be-41c6-9b67-075060e7b002 · outbound

This paper cites End-to-end learning of motion representation for video understanding.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices End-to-end learning of motion representation for video understanding

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.919331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.973097Z digest=sha256:2c21eead9c2a55fdf4a2b7e0fb4ce13238fa61a007113d0e5d57dbba450d5722

Observation b0b4b787-832a-4f4d-81e4-de3081d13c44 · outbound

This paper cites Starflow: A spatiotemporal recurrent cell for lightweight multi-frame optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Starflow: A spatiotemporal recurrent cell for lightweight multi-frame optical flow estimation

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.908966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.976845Z digest=sha256:3687152ac9187b24da4efceae1c5b8d593e0ab139100ff100e123f09b783331f

Observation 0f632df4-6f31-4207-9def-5596731ccb30 · outbound

This paper cites Rethinking channel dimensions for efficient model design.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Rethinking channel dimensions for efficient model design

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.898900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.980349Z digest=sha256:16bb8f84253d48a84229dbcf16c8a5dc7ce193607282be8c5fad0dcdc4eee949

Observation 22fa44dd-f952-4fbd-96f5-e8c6e9fa6f1e · outbound

This paper cites Improving optical flow on a pyramid level.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Improving optical flow on a pyramid level

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.887958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.984032Z digest=sha256:daf3b522728cfc7755b520a6b0075e536f05e1d6735a33afdc1d3188f431a344

Observation cef5443f-269a-48db-8b56-b297263464ee · outbound

This paper cites Determining optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Determining optical flow

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.877508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.988092Z digest=sha256:fdebca94530081b76ffd33823e95f323300e2094bdd494bd25b8cfafe26cddb1

Observation e46df64c-4263-4c5a-b9c3-e7a776c2f160 · outbound

This paper cites Searching for mo- bilenetv3.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Searching for mo- bilenetv3

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.867454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.991842Z digest=sha256:5e75e49f493dfca9a3d7b83a7a1b13ae89e49a24e5a461a657ff1a899e077169

Observation 49e9c8f5-79c9-4fd0-ad91-1732b2a8982d · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:30.995455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:30.995455Z digest=sha256:c177e8ad052419ce8dd6d8c9ee6ae4b6526953e93e4456112054328d7fccd0bd

Observation 773634d6-fb33-4e22-949e-5a4c856c6d70 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Flowformer: A transformer architecture for optical flow

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.856403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:30.999881Z digest=sha256:69f09ec464dee0165a3bc792384393da8fb3e8f448fff797e936ec541d9a1dbf

Observation 79ed9ab6-83c4-42d9-95da-0d0f30aef6e1 · outbound

This paper cites Liteflownet3: Resolving correspondence ambiguity for more accurate optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Liteflownet3: Resolving correspondence ambiguity for more accurate optical flow estimation

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.845258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.003603Z digest=sha256:d7df9767162e4954195023e609a94b8e720f1a49fcac1d4ec2c3b95de9e68964

Observation 5c770b5f-1c43-4853-bcb7-3f605d6ee5ec · outbound

This paper cites Lite- FlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Lite- FlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.833765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.007796Z digest=sha256:c22f1da1a4924862f556e69e69f44916e59ecd07e27151ebf0b654797c8917ea

Observation e07931da-2f6a-4cfa-aadd-3eca010ebe11 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Iterative residual refinement for joint optical flow and occlusion estimation

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.822353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.011890Z digest=sha256:8262fb6616b510f34c280d6c5e8a99338f65f6d438183353f0068e14fe880e22

Observation 505e775f-f054-4802-91a3-f98a607dd378 · outbound

This paper cites Ai benchmark: Running deep neural networks on android smartphones.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Ai benchmark: Running deep neural networks on android smartphones

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.811155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.016241Z digest=sha256:8dff3c5d5c2d18fdddf057338d7653f80a757cd90058e162b6e8b9df627ac4de

Observation 717341e4-9a6f-4861-8309-4597bfbf16ce · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Flownet 2.0: Evolution of optical flow estimation with deep networks

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.796932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.020087Z digest=sha256:c8966f30a17c7e1c3f07b6408dde38251280b95c9ce67218863f8f4c26d12666

Observation 9761a8b7-ee6c-414a-93ae-5905bb76c019 · outbound

This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.023748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.023748Z digest=sha256:ae5bffc6bd86da9faea1dd4d27364cfd83e1399db515b04830db4801dccc1ae7

Observation 210f39ed-ad09-4c0b-b31b-b101c1cc48b6 · outbound

This paper cites Unsupervised learning of multi-frame optical flow with occlusions.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Unsupervised learning of multi-frame optical flow with occlusions

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.785537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.027786Z digest=sha256:57c6a6086df575ac5189ce5322e588ef8f44281e83693b8bb5f38a31cd517e94

Observation 9b3292ea-8da9-4280-99c5-776f086b9e90 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Learning to estimate hidden motions with global motion aggregation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.773472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.031614Z digest=sha256:d98643221221b635254a9cbf88e99ec2bf8c8b10eacfeb1bac6aa9006cecc4c2

Observation 154df96e-fca9-42f9-bb92-d3e13bc94683 · outbound

This paper cites The hci benchmark suite: Stereo and flow ground truth with uncertainties for urban autonomous driving.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices The hci benchmark suite: Stereo and flow ground truth with uncertainties for urban autonomous driving

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.760685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.035462Z digest=sha256:2381f2292cd2f24b7699ce9b04bb88803c127bce86a564265e07d8a11119b48c

Observation bd0dbdc0-8445-43b5-a94b-3c53470273dc · outbound

This paper cites Fdflownet: Fast optical flow estimation using a deep lightweight network.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Fdflownet: Fast optical flow estimation using a deep lightweight network

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.748028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.039324Z digest=sha256:73843b2fd29d4db866dae68454e44e6c9beb2debcef68bfd681f186ba7efb6a9

Observation 2f64f808-cc1e-435b-8cb8-9e7e38c020f2 · outbound

This paper cites Fastflownet: A lightweight network for fast optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Fastflownet: A lightweight network for fast optical flow estimation

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.736635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.043470Z digest=sha256:1dd5cf8f01dd24c6d335b46790bda46d3b3e2bd9d048a413b8b4906c0cbc59d9

Observation 83cd9617-bdc7-45db-ab29-61615409a548 · outbound

This paper cites Fast optical flow using dense inverse search.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Fast optical flow using dense inverse search

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.725267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.047347Z digest=sha256:1fa136fc352f84bd9929715c991014448c5429ef46ee772cb7f7774635c458ad

Observation 99b0df72-a44b-4fbb-8107-0444899572b8 · outbound

This paper cites On-Device Neural Net Inference with Mobile GPUs.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices On-Device Neural Net Inference with Mobile GPUs

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.051248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.051248Z digest=sha256:eef39a50a7124ca7044bba13b6bde6106a2605b10a60813a87f2bebfc0de9c75

Observation 7a662570-b552-4902-9b97-14b3eac143c1 · outbound

This paper cites Centermask: Real-time anchor-free instance segmentation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Centermask: Real-time anchor-free instance segmentation

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.714640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.055368Z digest=sha256:f25697fcf540d0d407185b3dcb1a9fadb48cb1658f756858ce11484007f15ddf

Observation 2bcd703c-c273-4723-9e0a-f012a16d537f · outbound

This paper cites An energy and gpu-computation efficient backbone network for real-time object detection.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices An energy and gpu-computation efficient backbone network for real-time object detection

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.059175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.059175Z digest=sha256:11419fb1cf991bcc9b5d7727030e3b406de5ab656d62a4cde270fcb0deda4c70

Observation a0ef2c4e-0f1a-44e5-8ffd-cb0ce5de299f · outbound

This paper cites Efficient- former: Vision transformers at mobilenet speed.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Efficient- former: Vision transformers at mobilenet speed

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.697010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.062940Z digest=sha256:ca0bdea6db81de20f8f345816a4ef660315ff16df5624f02b3e8ef99c916ce99

Observation a3de0e48-e93d-43ff-a87b-2364abde4190 · outbound

This paper cites Gaflow: Incorporating gaussian attention into optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Gaflow: Incorporating gaussian attention into optical flow

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.686287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.066724Z digest=sha256:2fcae2e80c776afa5e335ed81eccc0f710b1e2a826e07390b46a4004d3b750ee

Observation dbeca0d9-bf27-42aa-8fc6-0078ab1b6725 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.674492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.070472Z digest=sha256:758c70868290b4fd274b7458ec02fccbd3355831527995cba2cad424f5ffa7e3

Observation cb14652a-8b55-4e33-85c4-8ae3b5a76a35 · outbound

This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.074234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.074234Z digest=sha256:d2183e1ec16959cef51fee9a14c59117ed313b996c9460e854a46c5a2df59a8e

Observation b1c18878-6789-4b3e-b7ca-91b295c4269b · outbound

This paper cites Object scene flow for autonomous vehicles.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Object scene flow for autonomous vehicles

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.663776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.078371Z digest=sha256:bda530526c9a677f539de43d20933ce56980cb92ad6aaba726e7d56d59c20500

Observation 238e72b4-63f5-4caa-9223-2d6a1173a747 · outbound

This paper cites Hardcore-nas: Hard constrained differentiable neural architec- ture search.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Hardcore-nas: Hard constrained differentiable neural architec- ture search

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.651373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.082273Z digest=sha256:6ba18176450fc7ce0005c1d3aff8ca8b55fca10a5a7708d307c1768b488ec083

Observation 79c53095-bd34-47a7-b468-60e7cab0bc2d · outbound

This paper cites Context-aware synthesis for video frame interpolation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Context-aware synthesis for video frame interpolation

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.637980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.085912Z digest=sha256:f3be450d887616607cd7c0b6669450a4514697c75eaa95e60008a2394ec0499e

Observation d1151741-052a-453e-be27-55846cf65404 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Pytorch: An imperative style, high-performance deep learning library

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.625751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.089626Z digest=sha256:c8c860cf1d4ef5fa3829256771fdfe201ecf116abe0a9df9b30322848b1aa596

Observation 89db1f88-8405-45d1-b2fb-d5a905082047 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Optical flow estimation using a spatial pyramid network

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.613397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.093295Z digest=sha256:035e159c96b829157d22d320fb661864f5aa0113250f9247394573bea8874db5

Observation 427660fe-0012-4920-a3a6-4bf153a01909 · outbound

This paper cites Sudderth, and Jan Kautz.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Sudderth, and Jan Kautz

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.600700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.096933Z digest=sha256:2506ea8e099facc2750edaad2fdc69a01878eea36e4d8b4aab84a39e3b3a856d

Observation a766e97e-bcb7-499b-aa02-96231144609c · outbound

This paper cites Richter, Zeeshan Hayder, and Vladlen Koltun.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Richter, Zeeshan Hayder, and Vladlen Koltun

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.589111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.100831Z digest=sha256:918ed817b23454d2d5d2bd93c48203f3f5343054f248345e37f78663252676af

Observation 6a389aa1-538d-41e9-b41a-ab608e79a782 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.104539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.104539Z digest=sha256:eed2b9feb5f1db9ab50eb19767b3adbf04534ab27dfc5f262a441dd33b560e2f

Observation 13ee8789-fa11-4f17-b49b-18bdb8c75279 · outbound

This paper cites VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.108226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.108226Z digest=sha256:726b4bcd8ed00c50713b85cab04186f54314734094068b992822365a05359b15

Observation 28246f79-b74a-4e9c-9d6c-3d7bf28e99f2 · outbound

This paper cites FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-11T13:22:31.256508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.112270Z digest=sha256:ec29a1357b0be1a8bc3312afebad58cb27f49a42771ba816823e914e32e10a7b

Observation df89dd57-b544-47a0-9f88-5286dfa0ec63 · outbound

This paper cites Fine-grained motion representation for template-free visual tracking.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Fine-grained motion representation for template-free visual tracking

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.569275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.117152Z digest=sha256:2e6ed8764577643a093b5779d27101f1f78c69bbcc048b20196d0c98ff56ebfd

Observation b1afbc8d-c3e8-4cf3-979d-e3006fc62112 · outbound

This paper cites Two-stream con- volutional networks for action recognition in videos.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Two-stream con- volutional networks for action recognition in videos

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.557544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.121048Z digest=sha256:c105d1ac80af4456f0b1db06ae15e601948c89343f0842c812606b72bfa65750

Observation a917b090-8706-448f-987a-3958c6ca4dbd · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.124552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.124552Z digest=sha256:ae3c4f1498d459863f85acea491d5a6bc72acaab5037b790041cc86064537842

Observation f67bb8ec-370e-467d-8439-5838a020f0fa · outbound

This paper cites Models matter, so does training: An empirical study of cnns for optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Models matter, so does training: An empirical study of cnns for optical flow estimation

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.538079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.128573Z digest=sha256:eef596cdca342b52fe74bb1e39a866f918a934f21168fb1b66c8a427537fc8cb

Observation 543f52c8-5e57-43ea-9552-11c7e51abce4 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Autoflow: Learning a better training set for optical flow

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.526123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.132568Z digest=sha256:07f6f42274b02a2c2f6a0998578efc5e643eafe65a42d32a80790c363787f2dc

Observation 48706906-9c96-4147-a530-a2348b043d9e · outbound

This paper cites Disentan- gling architecture and training for optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Disentan- gling architecture and training for optical flow

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.514240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.137337Z digest=sha256:ff929066ed54f765e0a605e92f75137259e043383cfcd54937d4f925ca979ab7

Observation b029a137-d619-4b3d-8c67-1379e1bc160c · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.141120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.141120Z digest=sha256:820e5dd0c3b1107b10256c16f86043e640e6073606abc22bc2735271ed383ebd

Observation d4a90046-c833-4aa6-beff-d695208a8c68 · outbound

This paper cites Efficientnetv2: Smaller models and faster training.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Efficientnetv2: Smaller models and faster training

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.494681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.145029Z digest=sha256:375916b1342708c3a97f4861e7472fc30ebf7713c069f7f3e4c7e3a0ee9378db

Observation 29d2549e-32af-4f8d-9d7b-d944eb7a4cb1 · outbound

This paper cites MixConv: Mixed Depthwise Convolutional Kernels.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices MixConv: Mixed Depthwise Convolutional Kernels

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.148678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.148678Z digest=sha256:4338a774dade6a6894a76a538e1f1eead5208bfd01fb2204adffff39d16a0da4

Observation 789fb2bc-0b7d-4591-9f93-de34a2e80ddf · outbound

This paper cites Mnasnet: Platform-aware neural architecture search for mobile.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Mnasnet: Platform-aware neural architecture search for mobile

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.482016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.152987Z digest=sha256:6820754722ae47a62ab52270b3d0a84415a5203392298d817c2c0475bb29a856

Observation 151b5609-6ec7-4f46-9d0c-70f2958ed775 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Raft: Recurrent all-pairs field transforms for optical flow

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.468307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.156422Z digest=sha256:b44f00508972a1aa54358c9c479485197315cb8a44658bfe51893b8bca8ce3d4

Observation 93992dcf-987b-4694-92d4-f32a21b0699f · outbound

This paper cites Wadekar and Abhishek Chaurasia.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Wadekar and Abhishek Chaurasia

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.456348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.160101Z digest=sha256:371c09211a352f22d4cae9bb6440e3ea0b3be0405ee83a8d67d36b4666956c77

Observation e37bf8b3-206b-44a6-a907-fd73dceadd75 · outbound

This paper cites Correlation flow: robust optical flow using kernel cross- correlators.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Correlation flow: robust optical flow using kernel cross- correlators

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.445153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.164130Z digest=sha256:f2175b24caa028bd7046584e4b4fb21ebb702fb7ec591ee5d1b5e6be6538108d

Observation 1edfcd7a-0823-4213-afcb-94a8e02e5f57 · outbound

This paper cites Fbnet: Hardware-aware efficient con- vnet design via differentiable neural architecture search.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Fbnet: Hardware-aware efficient con- vnet design via differentiable neural architecture search

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.433512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.167986Z digest=sha256:0dd325bde242102baf9a7248f1bc07e2af8da168ed0bf905d7d0d0d74d68fca3

Observation 672605c9-cec4-46eb-a66b-56c7b918d750 · outbound

This paper cites High-resolution optical flow from 1d attention and correlation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices High-resolution optical flow from 1d attention and correlation

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.421323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.172218Z digest=sha256:a6f538e977e517844685a97a7b987b52554a6054a56aecb0775fc4aab0bf3382

Observation 6f3dc381-63cf-45c7-93fc-7ed140587ab5 · outbound

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

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Gmflow: Learning optical flow via global matching

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.175720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.175720Z digest=sha256:f22080941f42dd5c999545ed2671d36e3da5c69634344943a71e640bc478082e

Observation 0eb63692-bccd-4d84-a378-ca9c22a5889e · outbound

This paper cites Accurate optical flow via direct cost volume processing.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Accurate optical flow via direct cost volume processing

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.403210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.179685Z digest=sha256:701cad0ba275da5af978e980960c5329c7e30b1ffea3eb50163756ab144b9a12

Observation 2b45b7b6-f24a-4d63-98a3-72ceb2cc5c6e · outbound

This paper cites Video enhancement with task-oriented flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Video enhancement with task-oriented flow

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.391613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.183269Z digest=sha256:367803b8ace7a39f8e02461a74c8dbfc343bc93e2420bedd4c718471bf7cfa07

Observation 1e8aa6d3-393a-48ae-b883-db1c3c61088a · outbound

This paper cites V olumetric correspon- dence networks for optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices V olumetric correspon- dence networks for optical flow

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.377677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.187015Z digest=sha256:eb31eea8517e4c12ad41321ae4c322243b117d4e8b3bec6b3871d98f66b993ef

Observation 675a12fa-dc0f-4135-a711-f41520f32b31 · outbound

This paper cites Unsupervised motion representation enhanced network for action recogni- tion.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Unsupervised motion representation enhanced network for action recogni- tion

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.364869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.190688Z digest=sha256:3fc4a8bf71a0599fc9e034df7c6e26d5b55e33fc6c226c3b7661ff1dfa0b5bfe

Observation 43aa2a85-2502-4eac-80ff-ec5640664d8d · outbound

This paper cites Learning video stabiliza- tion using optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Learning video stabiliza- tion using optical flow

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.352907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.194562Z digest=sha256:acf4766d90f58424c338139b8043aed327b550ee0f9952086d24a0a6ae1eb631

Observation ccc5dc40-c074-4b2b-b726-f2b7740a1f9c · outbound

This paper cites A du- ality based approach for realtime tv-l 1 optical flow.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices A du- ality based approach for realtime tv-l 1 optical flow

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.341731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.198224Z digest=sha256:6efa064aceb1e68dc4a4c0d23d287bcd84c925532932ce6ab691db0c4f8f401e

Observation 0634b600-02eb-49f3-9bc0-e12f6a9b8820 · outbound

This paper cites Separable flow: Learning motion cost volumes for optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Separable flow: Learning motion cost volumes for optical flow estimation

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T13:22:31.330077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T13:22:31.201923Z digest=sha256:26af28da28518f862b4223420defb5de8edb7273eb0233d2d4602325afe64d74

Observation cceed588-2d9c-4c37-b8ca-db62c56c2742 · outbound

This paper cites Global matching with overlapping at- tention for optical flow estimation.

CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices Global matching with overlapping at- tention for optical flow estimation

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-11T13:22:31.205522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:22:31.205522Z digest=sha256:b79eb228780b26a7917f18d8ee82379b1aee822282f8647e1b7bdabefc262059

Pith citing papers

No inbound Pith citation observations are available.