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 451–500 of 2184 papers

TitleStatusHype
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-ResolutionCode1
Deficiency-Aware Masked Transformer for Video InpaintingCode1
DEFLOW: Self-supervised 3D Motion Estimation of Debris FlowCode1
Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationCode1
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
End-to-end Multi-modal Video Temporal GroundingCode1
Three-Stream 3D/1D CNN for Fine-Grained Action Classification and Segmentation in Table TennisCode1
EM-driven unsupervised learning for efficient motion segmentationCode1
Delving into Crispness: Guided Label Refinement for Crisp Edge DetectionCode1
Beyond a Video Frame Interpolator: A Space Decoupled Learning Approach to Continuous Image TransitionCode1
BubbleML: A Multi-Physics Dataset and Benchmarks for Machine LearningCode1
End-to-End Video Object Detection with Spatial-Temporal TransformersCode1
Towards Robust Monocular Visual Odometry for Flying Robots on Planetary MissionsCode1
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable AlignmentCode1
Dense Continuous-Time Optical Flow from Events and FramesCode1
Broaden Your Views for Self-Supervised Video LearningCode1
TTVOS: Lightweight Video Object Segmentation with Adaptive Template Attention Module and Temporal Consistency LossCode1
BF-STVSR: B-Splines and Fourier-Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
A New Dataset and Transformer for Stereoscopic Video Super-ResolutionCode1
Bringing Rolling Shutter Images Alive with Dual Reversed DistortionCode1
Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video RestorationCode1
E-RAFT: Dense Optical Flow from Event CamerasCode1
Unsupervised Joint Learning of Optical Flow and Intensity with Event CamerasCode1
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving VideosCode1
Unsupervised Video Object Segmentation via Prototype Memory NetworkCode1
Efficient Video Deblurring Guided by Motion MagnitudeCode1
Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance SystemsCode1
Enhanced Bi-directional Motion Estimation for Video Frame InterpolationCode1
Blind Video Temporal Consistency via Deep Video PriorCode1
FlowReg: Fast Deformable Unsupervised Medical Image Registration using Optical FlowCode1
Learning Cross-Scale Weighted Prediction for Efficient Neural Video CompressionCode1
Video Abnormal Event Detection by Learning to Complete Visual Cloze TestsCode1
Optical Flow Based Motion Detection for Autonomous DrivingCode1
An End-to-End Two-Stream Network Based on RGB Flow and Representation Flow for Human Action Recognition—0
Bridge Frame and Event: Common Spatiotemporal Fusion for High-Dynamic Scene Optical Flow—0
2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework—0
Bregman Iteration for Correspondence Problems: A Study of Optical Flow—0
Breaking The Ice: Video Segmentation for Close-Range Ice-Covered Waters—0
An End-to-End Edge Aggregation Network for Moving Object Segmentation—0
Efficient Neuromorphic Signal Processing with Loihi 2—0
Boundary Flow: A Siamese Network that Predicts Boundary Motion without Training on Motion—0
An Empirical Study of Visual Features for DNN based Audio-Visual Speech Enhancement in Multi-talker Environments—0
Devon: Deformable Volume Network for Learning Optical Flow—0
A 3D Morphable Model of Craniofacial Shape and Texture Variation—0
DeVOS: Flow-Guided Deformable Transformer for Video Object Segmentation—0
Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark—0
Detection of (Hidden) Emotions from Videos using Muscles Movements and Face Manifold Embedding—0
An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes—0
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All datasetsSintel-cleanSintel-finalKITTI 2015 (train)KITTI 2015KITTI 2012SpringSintel Clean unsupervisedSintel Final unsupervisedKITTI 2015 unsupervisedKITTI 2012 unsupervised

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