FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow | Paper Citation Record

Observation a2ad69eb-6058-40c9-bbc5-f4f35da8b5fb · outbound

This paper cites Learning optical flow from still images.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Learning optical flow from still images

Reference 1

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Observation f86003f7-9bfd-443d-b3d7-a0ef97083264 · outbound

This paper cites A computational framework and an algorithm for the measurement of visual motion.IJCV, 2:283–310, 1989.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow A computational framework and an algorithm for the measurement of visual motion.IJCV, 2:283–310, 1989

Reference 2

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Observation 748d52ba-52ad-41cc-bd76-7cc3e2a9a994 · outbound

This paper cites MEM- FOF: High-resolution training for memory-efficient multi-frame optical flow estima- tion.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow MEM- FOF: High-resolution training for memory-efficient multi-frame optical flow estima- tion

Reference 3

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Observation fb69b4f1-64e8-4a72-9951-06cc03871c35 · outbound

This paper cites PMBP: Patch- match belief propagation for correspondence problems.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow PMBP: Patch- match belief propagation for correspondence problems

Reference 4

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Observation 1485c4b5-4d7b-4225-be2d-befd9a9d55d7 · outbound

This paper cites A framework for the robust estimation of optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow A framework for the robust estimation of optical flow

Reference 5

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Observation be61ef6f-e2fd-4c78-bc61-8e5d992eabf1 · outbound

This paper cites High accuracy optical flow estimation based on a theory for warping.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow High accuracy optical flow estimation based on a theory for warping

Reference 6

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Observation 614f9eb5-660b-4dd4-9598-6bbf7b848235 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow A naturalistic open source movie for optical flow evaluation

Reference 7

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Observation 258cdc90-8fb7-4d12-a38e-af5c57de1653 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Sinkhorn distances: Lightspeed computation of optimal transport

Reference 8

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Observation 7b49862c-9dd9-4ffc-bf9c-b0374e39d51e · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Explicit motion disentangling for efficient optical flow estimation

Reference 9

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Observation 07ca7231-2448-4321-ac08-be017a66f5e6 · outbound

This paper cites Memflow: Optical flow estimation and prediction with memory.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Memflow: Optical flow estimation and prediction with memory

Reference 10

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Observation f9aa2b8c-67dd-4ef6-9d10-536f75d44888 · outbound

This paper cites Rethinking optical flow from geometric matching consistent perspective.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Rethinking optical flow from geometric matching consistent perspective

Reference 11

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Observation 972e14d7-4225-431f-989c-ae9139747968 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow FlowNet: Learning optical flow with convolutional networks

Reference 12

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Observation 15b01402-706c-467f-8cc8-6204d373a4b6 · outbound

This paper cites Flow-edge guided video completion.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Flow-edge guided video completion

Reference 13

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Observation 886c6526-0113-4db8-834e-a7b49049abe2 · outbound

This paper cites Vision meets robotics: The KITTI dataset.IJCV, 32(11):1231–1237, 2013.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Vision meets robotics: The KITTI dataset.IJCV, 32(11):1231–1237, 2013

Reference 14

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Observation c80e85f4-e943-4ba4-bf77-b0745ab0e710 · outbound

This paper cites RealFlow: EM-based realistic optical flow dataset generation from videos.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow RealFlow: EM-based realistic optical flow dataset generation from videos

Reference 15

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Observation f4ad1be3-ab1f-4cef-8de9-c25d2ec77245 · outbound

This paper cites Determining optical flow.Artificial intelli- gence, 17(1-3):185–203, 1981.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Determining optical flow.Artificial intelli- gence, 17(1-3):185–203, 1981

Reference 16

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Observation 5dd0fd85-4c2a-4ec2-87cf-31c7833de2ca · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow FlowFormer: A transformer architecture for optical flow

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 4ff981ab-39d6-4f78-92d6-c48e639e1929 · outbound

This paper cites Real-time intermediate flow estimation for video frame interpolation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Real-time intermediate flow estimation for video frame interpolation

Reference 18

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Observation 4bdaa668-3402-4cd4-9c24-2d318e891f95 · outbound

This paper cites LiteFlowNet3: Resolving Correspondence Ambi- guity for More Accurate Optical Flow Estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow LiteFlowNet3: Resolving Correspondence Ambi- guity for More Accurate Optical Flow Estimation

Reference 19

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Observation 6430b978-4296-425e-9720-e1dbff9711a5 · outbound

This paper cites LiteFlowNet: A Lightweight Con- volutional Neural Network for Optical Flow Estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow LiteFlowNet: A Lightweight Con- volutional Neural Network for Optical Flow Estimation

Reference 20

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Observation aa51cd00-de4d-4146-b8d7-d2baa8973a62 · outbound

This paper cites A Lightweight Optical Flow CNN —Revisiting Data Fidelity and Regularization .IEEE TPAMI, 43(08):2555–2569,.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow A Lightweight Optical Flow CNN —Revisiting Data Fidelity and Regularization .IEEE TPAMI, 43(08):2555–2569,

Reference 21

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Observation 8ee5af4d-1e47-482d-8ef2-98a3a187d1a0 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow FlowNet 2.0: Evolution of optical flow estimation with deep networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation f4e9913e-b565-4c18-980d-d287e0f511ca · outbound

This paper cites CCMR: High reso- lution optical flow estimation via coarse-to-fine context-guided motion reasoning.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow CCMR: High reso- lution optical flow estimation via coarse-to-fine context-guided motion reasoning

Reference 23

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Observation abd79a51-8a3d-46ed-9804-0356409caeb0 · outbound

This paper cites MS- RAFT+: high resolution multi-scale raft.IJCV, 132(5):1835–1856, 2024.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow MS- RAFT+: high resolution multi-scale raft.IJCV, 132(5):1835–1856, 2024

Reference 24

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Observation 511ec5cd-ec8b-4697-86ee-0fa7a9cc3417 · outbound

This paper cites Computer vision for autonomous vehicles: Problems, datasets and state of the art.Foundations and trends® in computer graphics and vision, 12(1–3):1–308, 2020.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Computer vision for autonomous vehicles: Problems, datasets and state of the art.Foundations and trends® in computer graphics and vision, 12(1–3):1–308, 2020

Reference 25

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Observation 07713d32-bca9-452c-a52d-7360de05a380 · outbound

This paper cites DistractFlow: Improving optical flow estimation via realistic distractions and pseudo-labeling.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow DistractFlow: Improving optical flow estimation via realistic distractions and pseudo-labeling

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 5b56373a-814f-4205-8da2-7297151bd4f5 · outbound

This paper cites Learning to Estimate Hidden Motions with Global Motion Aggregation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Learning to Estimate Hidden Motions with Global Motion Aggregation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 62852fa1-aee6-4b31-a7dc-be17600924b2 · outbound

This paper cites Learning optical flow from a few matches.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Learning optical flow from a few matches

Reference 28

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Observation dbe1f8f4-4ea5-465e-9fe4-758d57db72d7 · outbound

This paper cites EffiScene: Efficient per-pixel rigidity inference for unsupervised joint learning of optical flow, depth, camera pose and motion segmentation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow EffiScene: Efficient per-pixel rigidity inference for unsupervised joint learning of optical flow, depth, camera pose and motion segmentation

Reference 29

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Observation f54506fc-3fa3-42bc-b765-cc5a835ee9aa · outbound

This paper cites What matters in unsupervised optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow What matters in unsupervised optical flow

Reference 30

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Observation 4e5da885-31fe-4546-bc90-9ff55651aa0e · outbound

This paper cites AnyFlow: Arbitrary scale optical flow with implicit neural representation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow AnyFlow: Arbitrary scale optical flow with implicit neural representation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 5ef2554f-0e1a-45ed-a9a3-c7df731d6b3a · outbound

This paper cites Deep video inpaint- ing.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Deep video inpaint- ing

Reference 32

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Observation 859c6d61-a2e4-427a-b754-01acdf7d84b8 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow The HCI benchmark suite: Stereo and flow ground truth with uncertainties for urban autonomous driving

Reference 33

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Observation 4ed1c9ff-d185-49f9-86d8-597ef93d5d9d · outbound

This paper cites Win-Win: Training High-Resolution Vision Transformers from Two Windows.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Win-Win: Training High-Resolution Vision Transformers from Two Windows

Reference 34

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Observation ec9142ab-cc8b-4d96-bcc9-4e5d2f9c9a20 · outbound

This paper cites MegaDepth: Learning single-view depth prediction from internet photos.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow MegaDepth: Learning single-view depth prediction from internet photos

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 88924ddd-a059-4372-a033-66267cf68efa · outbound

This paper cites SIFT flow: Dense correspondence across scenes and its applications.IEEE TPAMI, 33(5):978–994, 2010.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow SIFT flow: Dense correspondence across scenes and its applications.IEEE TPAMI, 33(5):978–994, 2010

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 567c9336-5d5b-43a0-83bf-e486fcae8c30 · outbound

This paper cites ARFlow: Auto-regressive op- tical flow estimation for arbitrary-length videos via progressive next-frame forecasting.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow ARFlow: Auto-regressive op- tical flow estimation for arbitrary-length videos via progressive next-frame forecasting

Reference 37

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Observation 767008d8-fc6e-49cb-bfd9-cc7b0ca2fea6 · outbound

This paper cites Learning by analogy: Reliable su- pervision from transformations for unsupervised optical flow estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Learning by analogy: Reliable su- pervision from transformations for unsupervised optical flow estimation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 51cc41ea-c74e-437d-aa8e-4ccfb774aba2 · outbound

This paper cites Flow2Stereo: Effective self- supervised learning of optical flow and stereo matching.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Flow2Stereo: Effective self- supervised learning of optical flow and stereo matching

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation f2c7f6ba-4f7a-4148-8cd4-0907ee2ab8d5 · outbound

This paper cites Video frame interpolation via optical flow estimation with image inpainting.IJCV, 35(12):2087–2102, 2020.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Video frame interpolation via optical flow estimation with image inpainting.IJCV, 35(12):2087–2102, 2020

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation c341bdce-0760-41e4-bf8f-0c8f3dedae55 · outbound

This paper cites Decoupled Weight Decay Regularization.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Decoupled Weight Decay Regularization

Reference 41

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Observation 2596d95a-7ae5-40a1-81f8-a48238c73363 · outbound

This paper cites Learn- ing optical flow with adaptive graph reasoning.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Learn- ing optical flow with adaptive graph reasoning

Reference 42

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Observation 5c12ddbd-a14c-46c7-83fe-93bb8d99b8b1 · outbound

This paper cites FlowDif- fuser: Advancing optical flow estimation with diffusion models.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow FlowDif- fuser: Advancing optical flow estimation with diffusion models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation e8aeca86-e4fe-400e-baee-05e0b55ee02f · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation

Reference 44

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Observation a1db3777-9604-4102-950b-0df5e8c8a4c5 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Spring: A high-resolution high-detail dataset and benchmark for scene flow, optical flow and stereo

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation befac680-8c1d-4c0f-88a3-36a5b174b06a · outbound

This paper cites Object scene flow for autonomous vehicles.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Object scene flow for autonomous vehicles

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation db9a4539-db99-45b4-a902-b25e0eb75be7 · outbound

This paper cites Confidence aware stereo matching for realistic clut- tered scenario.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Confidence aware stereo matching for realistic clut- tered scenario

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation bcec8015-59be-4a55-966e-493afa7a3ef5 · outbound

This paper cites S2M2: Scalable stereo matching model for reliable depth estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow S2M2: Scalable stereo matching model for reliable depth estimation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 710c66f9-c99c-40e6-9c13-4f80c5298fd6 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Recurrent partial kernel network for efficient optical flow estimation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 6b69281f-072b-4aff-bc9e-9c00552fc647 · outbound

This paper cites DPFlow: Adaptive optical flow estimation with a dual-pyramid framework.arXiv preprint arXiv:2503.14880, 2025.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow DPFlow: Adaptive optical flow estimation with a dual-pyramid framework.arXiv preprint arXiv:2503.14880, 2025

Reference 50

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation ee45b440-431f-449e-9770-4cab1230b93f · outbound

This paper cites Automatic differentiation in PyTorch.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Automatic differentiation in PyTorch

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 4c7a608f-8988-46f5-8ca9-b6751ca2706f · outbound

This paper cites Representation flow for action recognition.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Representation flow for action recognition

Reference 52

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 21974c1f-a50b-4080-956b-8e178119158d · outbound

This paper cites FlowSeek: Optical flow made easier with depth founda- tion models and motion bases.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow FlowSeek: Optical flow made easier with depth founda- tion models and motion bases

Reference 53

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation d559bd79-bcc3-425a-b91b-7a6439e1ea56 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Optical flow estimation using a spatial pyramid network

Reference 54

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Observation 52b9fa15-72bb-4133-b630-e4ec513a2260 · outbound

This paper cites Playing for benchmarks.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Playing for benchmarks

Reference 55

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 6889bce6-dbdd-4c12-93f7-dd7a518f37aa · outbound

This paper cites SuperGlue: Learning feature matching with graph neural networks.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow SuperGlue: Learning feature matching with graph neural networks

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation 5f60ca40-0545-4d62-a049-d5f7b69a85ac · outbound

This paper cites The surprising effectiveness of diffusion models for optical flow and monocular depth estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow The surprising effectiveness of diffusion models for optical flow and monocular depth estimation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

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Observation e45832be-3b08-4158-8089-b24fc169c540 · outbound

This paper cites VideoFlow: Ex- ploiting temporal cues for multi-frame optical flow estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow VideoFlow: Ex- ploiting temporal cues for multi-frame optical flow estimation

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffc24b79-19d6-4ac0-b670-bba0af576dda · outbound

This paper cites Flowformer++: Masked cost volume autoencoding for pretraining optical flow estimation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Flowformer++: Masked cost volume autoencoding for pretraining optical flow estimation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4aadf461-cce4-4a74-bf8b-ef438d28804a · outbound

This paper cites Super-convergence: Very fast training of neural networks using large learning rates.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Super-convergence: Very fast training of neural networks using large learning rates

Reference 60

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a3351cc-6682-4df4-886f-f88042793165 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow CRAFT: Cross-attentional flow transformer for robust optical flow

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de53c83b-afbd-4708-b0f9-138dfd1195cf · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 009f214d-d3de-4a85-80f5-b0fa42f8431f · outbound

This paper cites Models matter, so does training: An empirical study of CNNs for optical flow estimation.IEEE TPAMI, 42(6): 1408–1423, 2019.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Models matter, so does training: An empirical study of CNNs for optical flow estimation.IEEE TPAMI, 42(6): 1408–1423, 2019

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7533243d-facf-4d95-8d2f-2bf61f73bc65 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow AutoFlow: Learning a better training set for optical flow

Reference 64

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c451a41-41ec-415f-9c0d-68ed7cd30a9d · outbound

This paper cites Disentangling architecture and training for optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Disentangling architecture and training for optical flow

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54e69830-e4b2-4aa6-9978-fcfce81a0f53 · outbound

This paper cites SKFlow: Learning optical flow with super kernels.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow SKFlow: Learning optical flow with super kernels

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bc63d98-678b-48cd-91e9-ae1be503c9e9 · outbound

This paper cites Streamflow: streamlined multi-frame optical flow estimation for video sequences.Ad- vances in neural information processing systems, 37:9205–9228, 2024.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Streamflow: streamlined multi-frame optical flow estimation for video sequences.Ad- vances in neural information processing systems, 37:9205–9228, 2024

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d3146c9-4053-4073-8a97-c92513f5c344 · outbound

This paper cites Optical flow guided feature: A fast and robust motion representation for video action recogni- tion.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Optical flow guided feature: A fast and robust motion representation for video action recogni- tion

Reference 68

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3087bc8-f233-4abf-8565-7e7cf2e6e13a · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow RAFT: Recurrent all-pairs field transforms for optical flow

Reference 69

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10aa021e-4ad9-4a61-90c3-d5b30e33f549 · outbound

This paper cites Splatflow: Learning multi-frame optical flow via splatting.International Journal of Computer Vision, 132(8):3023–3045, 2024.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Splatflow: Learning multi-frame optical flow via splatting.International Journal of Computer Vision, 132(8):3023–3045, 2024

Reference 70

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb807586-f651-4740-b4db-8624e40a727a · outbound

This paper cites TartanAir: A dataset to push the limits of visual SLAM.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow TartanAir: A dataset to push the limits of visual SLAM

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37177a57-c2fa-4b59-96a7-1f00dd06faf8 · outbound

This paper cites W AFT: Warping-alone field transforms for optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow W AFT: Warping-alone field transforms for optical flow

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d469b24-1dee-4eb8-bed6-e6766af95292 · outbound

This paper cites SEA-RAFT: Simple, efficient, accurate RAFT for optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow SEA-RAFT: Simple, efficient, accurate RAFT for optical flow

Reference 73

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 778cd0a5-e72c-4e36-adaf-4b773891177d · outbound

This paper cites CroCo v2: Improved cross-view completion pre-training for stereo matching and optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow CroCo v2: Improved cross-view completion pre-training for stereo matching and optical flow

Reference 74

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e1e4ee5-55d9-44df-aa6e-9373f25acfed · outbound

This paper cites Layeredflow: A real-world benchmark for non-lambertian multi-layer optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Layeredflow: A real-world benchmark for non-lambertian multi-layer optical flow

Reference 75

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9393183a-c39c-4745-8c23-18d4048b82e6 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow GMFlow: Learning optical flow via global matching

Reference 76

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bffa221a-3212-4e84-945e-75077282739d · outbound

This paper cites Unifying flow, stereo and depth estimation.IEEE TPAMI, 2023.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Unifying flow, stereo and depth estimation.IEEE TPAMI, 2023

Reference 77

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d7c2b68-6663-4bd6-9907-afd4a0d487fc · outbound

This paper cites YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark

Reference 78

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4740dc-8e98-4b83-a2b5-94ce50265aaa · outbound

This paper cites Deep flow-guided video inpainting.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Deep flow-guided video inpainting

Reference 79

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad063178-31d9-4642-b4d2-10e708bb727b · outbound

This paper cites Quadratic video interpolation.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Quadratic video interpolation

Reference 80

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 445d7e5a-9fac-45f8-a34b-1f03a8907a94 · outbound

This paper cites V olumetric correspondence networks for optical flow.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow V olumetric correspondence networks for optical flow

Reference 81

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7bc4272-7a4f-46f8-a20e-4ea94a84f245 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow A duality based approach for realtime tv-l1 optical flow

Reference 82

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d490d5a6-9706-4558-af6a-8b6d4b9fb5a5 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Global matching with overlapping attention for optical flow estimation

Reference 83

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cf42b7b-47ba-4af6-87b2-8e45f096b0f5 · outbound

This paper cites Improved two-stream model for human action recognition.EURASIP Journal on Image and Video Processing, 2020(1):1–9, 2020.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow Improved two-stream model for human action recognition.EURASIP Journal on Image and Video Processing, 2020(1):1–9, 2020

Reference 84

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a5b10b2-9bbc-4633-895b-f77bec139729 · outbound

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

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow DIP: Deep inverse patchmatch for high-resolution optical flow

Reference 85

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a38c2f04-abbc-460b-a5d3-d4f4098088a7 · outbound

This paper cites SamFlow: Eliminating any fragmen- tation in optical flow with segment anything model.

FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow SamFlow: Eliminating any fragmen- tation in optical flow with segment anything model

Reference 86

Resolution: unresolved; no resolver link, observed 2026-07-13T16:08:30.031334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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