SOTAVerified

Optical Flow Estimation

Optical Flow Estimation is a computer vision task that involves computing the motion of objects in an image or a video sequence. The goal of optical flow estimation is to determine the movement of pixels or features in the image, which can be used for various applications such as object tracking, motion analysis, and video compression.

Approaches for optical flow estimation include correlation-based, block-matching, feature tracking, energy-based, and more recently gradient-based.

Further readings:

Definition source: Devon: Deformable Volume Network for Learning Optical Flow

Image credit: Optical Flow Estimation

Papers

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Showing 2001–2050 of 2184 papers

TitleStatusHype
End-to-end Flow Correlation Tracking with Spatial-temporal Attention—0
End-to-End Interactive Prediction and Planning with Optical Flow Distillation for Autonomous Driving—0
Dynamic 3D Avatar Creation from Hand-held Video Input—0
End-to-End Learning for Video Frame Compression with Self-Attention—0
Zero-shot Hazard Identification in Autonomous Driving: A Case Study on the COOOL Benchmark—0
A diffusion and clustering-based approach for finding coherent motions and understanding crowd scenes—0
End-to-End Learning of Video Super-Resolution with Motion Compensation—0
Dyadic Movement Synchrony Estimation Under Privacy-preserving Conditions—0
End-to-end Neural Video Coding Using a Compound Spatiotemporal Representation—0
End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Intervention—0
Tracking in Crowd is Challenging: Analyzing Crowd based on Physical Characteristics—0
Dy3DGS-SLAM: Monocular 3D Gaussian Splatting SLAM for Dynamic Environments—0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs—0
A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation—0
Enhanced Correlation Matching based Video Frame Interpolation—0
Enhanced Frame and Event-Based Simulator and Event-Based Video Interpolation Network—0
Tracking Individual Targets in High Density Crowd Scenes Analysis of a Video Recording in Hajj 2009—0
Enhancing Bandwidth Efficiency for Video Motion Transfer Applications using Deep Learning Based Keypoint Prediction—0
Enhancing Dynamic CT Image Reconstruction with Neural Fields and Optical Flow—0
Enhancing Feature Tracking With Gyro Regularization—0
Enhancing Marine Debris Acoustic Monitoring by Optical Flow-Based Motion Vector Analysis—0
DualX-VSR: Dual Axial SpatialTemporal Transformer for Real-World Video Super-Resolution without Motion Compensation—0
EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow—0
Error-Aware Spatial Ensembles for Video Frame Interpolation—0
ES-MVSNet: Efficient Framework for End-to-end Self-supervised Multi-View Stereo—0
Estimating Dynamic Flow Features in Groups of Tracked Objects—0
Estimating motion with principal component regression strategies—0
Tracking of the Internal Jugular Vein in Ultrasound Images Using Optical Flow—0
Dual Semantic Fusion Network for Video Object Detection—0
Estimation of Clinical Workload and Patient Activity using Deep Learning and Optical Flow—0
Estimation of Linear Motion in Dense Crowd Videos using Langevin Model—0
eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks—0
Evaluation of the Spatio-Temporal features and GAN for Micro-expression Recognition System—0
EvConv: Fast CNN Inference on Event Camera Inputs For High-Speed Robot Perception—0
Duality-Gated Mutual Condition Network for RGBT Tracking—0
Event-based Moving Object Detection and Tracking—0
Tracking Virtual Meetings in the Wild: Re-identification in Multi-Participant Virtual Meetings—0
Dual approach for object tracking based on optical flow and swarm intelligence—0
Event-based Video Frame Interpolation with Edge Guided Motion Refinement—0
Event-based vision for egomotion estimation using precise event timing—0
Event-based vision on FPGAs -- a survey—0
Planar Velocity Estimation for Fast-Moving Mobile Robots Using Event-Based Optical Flow—0
DS-NeRV: Implicit Neural Video Representation with Decomposed Static and Dynamic Codes—0
EventDiff: A Unified and Efficient Diffusion Model Framework for Event-based Video Frame Interpolation—0
DroneAttention: Sparse Weighted Temporal Attention for Drone-Camera Based Activity Recognition—0
Training Datasets Generation for Machine Learning: Application to Vision Based Navigation—0
EventHDR: from Event to High-Speed HDR Videos and Beyond—0
Drift Robust Non-rigid Optical Flow Enhancement for Long Sequences—0
Training Deep SLAM on Single Frames—0
Transferring Dual Stochastic Graph Convolutional Network for Facial Micro-expression Recognition—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error6.64—Unverified
2FastFlowNet-ftAverage End-Point Error4.89—Unverified
3UnrolledCostAverage End-Point Error4.69—Unverified
4LiteFlowNet-ftAverage End-Point Error4.54—Unverified
5FlowNet2Average End-Point Error3.96—Unverified
6IRR-PWCAverage End-Point Error3.84—Unverified
7SelFlowAverage End-Point Error3.74—Unverified
8FDFlowNet-ftAverage End-Point Error3.71—Unverified
9ScopeFlowAverage End-Point Error3.59—Unverified
10LiteFlowNet2-ftAverage End-Point Error3.48—Unverified
#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error8.36—Unverified
2FastFlowNet-ftAverage End-Point Error6.08—Unverified
3UnrolledCostAverage End-Point Error5.8—Unverified
4MR-FlowAverage End-Point Error5.38—Unverified
5LiteFlowNet-ftAverage End-Point Error5.38—Unverified
6FDFlowNet-ftAverage End-Point Error5.11—Unverified
7LiteFlowNet2-ftAverage End-Point Error4.69—Unverified
8IRR-PWCAverage End-Point Error4.58—Unverified
9LiteFlowNet3-SAverage End-Point Error4.53—Unverified
10ContinualFlow + ftAverage End-Point Error4.52—Unverified
#ModelMetricClaimedVerifiedStatus
1PWC-NetF1-all33.7—Unverified
2FastFlowNetF1-all33.1—Unverified
3FlowNet2F1-all30—Unverified
4VCNF1-all25.1—Unverified
5HD3F1-all24—Unverified
6MaskFlowNetF1-all23.1—Unverified
7SCVF1-all19.3—Unverified
8RAPIDFlowF1-all17.7—Unverified
9CRAFTF1-all17.5—Unverified
10RAFTF1-all17.4—Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftFl-all11.22—Unverified
2UnrolledCostFl-all10.81—Unverified
3LiteFlowNet-ftFl-all9.38—Unverified
4SelFlowFl-all8.42—Unverified
5IRR-PWCFl-all7.65—Unverified
6LiteFlowNet2-ftFl-all7.62—Unverified
7LiteFlowNet3Fl-all7.34—Unverified
8LiteFlowNet3-SFl-all7.22—Unverified
9MaskFlownet-SFl-all6.81—Unverified
10RAPIDFlowFl-all6.12—Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftAverage End-Point Error1.8—Unverified
2LiteFlowNet-ftAverage End-Point Error1.6—Unverified
3IRR-PWCAverage End-Point Error1.6—Unverified
4SelFlowAverage End-Point Error1.5—Unverified
5FDFlowNet-ftAverage End-Point Error1.5—Unverified
6PWC-Net + ft - axXivAverage End-Point Error1.5—Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4—Unverified
8LiteFlowNet3-SAverage End-Point Error1.3—Unverified
9LiteFlowNet3Average End-Point Error1.3—Unverified
10MaskFlownetAverage End-Point Error1.1—Unverified
#ModelMetricClaimedVerifiedStatus
1PWCNet1px total82.27—Unverified
2SPyNet1px total29.96—Unverified
3GMFlow1px total10.36—Unverified
4GMA1px total7.07—Unverified
5RAFT1px total6.79—Unverified
6FlowNet21px total6.71—Unverified
7FlowFormer1px total6.51—Unverified
8MS-RAFT+1px total5.72—Unverified
9RPKNet1px total4.81—Unverified
10DPFlow1px total3.44—Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error5.21—Unverified
2MDFlow-FastAverage End-Point Error4.73—Unverified
3UpFlowAverage End-Point Error4.68—Unverified
4ARFlow-MVAverage End-Point Error4.49—Unverified
5MDFlowAverage End-Point Error4.16—Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error6.5—Unverified
2MDFlow-FastAverage End-Point Error5.99—Unverified
3ARFlow-MVAverage End-Point Error5.67—Unverified
4MDFlowAverage End-Point Error5.46—Unverified
5UpFlowAverage End-Point Error5.32—Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVFl-all11.79—Unverified
2MDFlow-FastFl-all11.43—Unverified
3UpFlowFl-all9.38—Unverified
4MDFlowFl-all8.91—Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVAverage End-Point Error1.5—Unverified
2UpFlowAverage End-Point Error1.4—Unverified