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

Showing 20012050 of 2184 papers

TitleStatusHype
SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground TruthCode0
Two-Stream Convolutional Networks for Dynamic Texture SynthesisCode0
Facial Expression Spotting Based on Optical Flow FeaturesCode0
Learning Temporal Pose Estimation from Sparsely-Labeled VideosCode0
Real-Time Image Analysis Software Suitable for Resource-Constrained ComputingCode0
Extending Information Bottleneck Attribution to Video SequencesCode0
SCSim: A Realistic Spike Cameras SimulatorCode0
SC-Transformer++: Structured Context Transformer for Generic Event Boundary DetectionCode0
SDC-Net: Video prediction using spatially-displaced convolutionCode0
Exploring Temporal Information for Improved Video UnderstandingCode0
Deep multi-scale video prediction beyond mean square errorCode0
AI-Driven Relocation Tracking in Dynamic Kitchen EnvironmentsCode0
Exploring Long- and Short-Range Temporal Information for Learned Video CompressionCode0
Learning Task-Specific Generalized Convolutions in the Permutohedral LatticeCode0
SDOF-Tracker: Fast and Accurate Multiple Human Tracking by Skipped-Detection and Optical-FlowCode0
Exploration via Flow-Based Intrinsic RewardsCode0
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field EstimationCode0
Optical Flow Dataset and Benchmark for Visual Crowd AnalysisCode0
Two-Stream Action Recognition-Oriented Video Super-ResolutionCode0
Variational Approach for Capsule Video Frame InterpolationCode0
EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion SaliencyCode0
Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion PriorCode0
Bridging Stereo Matching and Optical Flow via Spatiotemporal CorrespondenceCode0
Learning Optical Expansion From Scale MatchingCode0
SegFlow: Joint Learning for Video Object Segmentation and Optical FlowCode0
Synthetic Data Generation for 3D Myocardium Deformation AnalysisCode0
Learning on the Edge: Explicit Boundary Handling in CNNsCode0
Segmentation-Aware Convolutional Networks Using Local Attention MasksCode0
A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame PredictionCode0
Ada-Tracker: Soft Tissue Tracking via Inter-Frame and Adaptive-Template MatchingCode0
ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation with Zero-Shot MethodCode0
Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action RecognitionCode0
Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVsCode0
EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based CamerasCode0
Self-Calibrating 4D Novel View Synthesis from Monocular Videos Using Gaussian SplattingCode0
TadML: A fast temporal action detection with Mechanics-MLPCode0
A Numerical Framework for Efficient Motion Estimation on Evolving Sphere-Like Surfaces based on Brightness and Mass Conservation LawsCode0
SelFlow: Self-Supervised Learning of Optical FlowCode0
Optical Flow on Evolving Sphere-Like SurfacesCode0
Video Acceleration MagnificationCode0
Uncertainty Estimates and Multi-Hypotheses Networks for Optical FlowCode0
Deep motion estimation for parallel inter-frame prediction in video compressionCode0
Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic UnderstandingCode0
Optical Flow Requires Multiple Strategies (but only one network)Code0
Event TransformerCode0
VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAECode0
Event Neural NetworksCode0
Learning Multi-Human Optical FlowCode0
EventGAN: Leveraging Large Scale Image Datasets for Event CamerasCode0
A Database and Evaluation Methodology for Optical FlowCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error6.64Unverified
2FastFlowNet-ftAverage End-Point Error4.89Unverified
3UnrolledCostAverage End-Point Error4.69Unverified
4LiteFlowNet-ftAverage End-Point Error4.54Unverified
5FlowNet2Average End-Point Error3.96Unverified
6IRR-PWCAverage End-Point Error3.84Unverified
7SelFlowAverage End-Point Error3.74Unverified
8FDFlowNet-ftAverage End-Point Error3.71Unverified
9ScopeFlowAverage End-Point Error3.59Unverified
10LiteFlowNet2-ftAverage End-Point Error3.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error8.36Unverified
2FastFlowNet-ftAverage End-Point Error6.08Unverified
3UnrolledCostAverage End-Point Error5.8Unverified
4MR-FlowAverage End-Point Error5.38Unverified
5LiteFlowNet-ftAverage End-Point Error5.38Unverified
6FDFlowNet-ftAverage End-Point Error5.11Unverified
7LiteFlowNet2-ftAverage End-Point Error4.69Unverified
8IRR-PWCAverage End-Point Error4.58Unverified
9LiteFlowNet3-SAverage End-Point Error4.53Unverified
10ContinualFlow + ftAverage End-Point Error4.52Unverified
#ModelMetricClaimedVerifiedStatus
1PWC-NetF1-all33.7Unverified
2FastFlowNetF1-all33.1Unverified
3FlowNet2F1-all30Unverified
4VCNF1-all25.1Unverified
5HD3F1-all24Unverified
6MaskFlowNetF1-all23.1Unverified
7SCVF1-all19.3Unverified
8RAPIDFlowF1-all17.7Unverified
9CRAFTF1-all17.5Unverified
10RAFTF1-all17.4Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftFl-all11.22Unverified
2UnrolledCostFl-all10.81Unverified
3LiteFlowNet-ftFl-all9.38Unverified
4SelFlowFl-all8.42Unverified
5IRR-PWCFl-all7.65Unverified
6LiteFlowNet2-ftFl-all7.62Unverified
7LiteFlowNet3Fl-all7.34Unverified
8LiteFlowNet3-SFl-all7.22Unverified
9MaskFlownet-SFl-all6.81Unverified
10RAPIDFlowFl-all6.12Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftAverage End-Point Error1.8Unverified
2LiteFlowNet-ftAverage End-Point Error1.6Unverified
3IRR-PWCAverage End-Point Error1.6Unverified
4SelFlowAverage End-Point Error1.5Unverified
5FDFlowNet-ftAverage End-Point Error1.5Unverified
6PWC-Net + ft - axXivAverage End-Point Error1.5Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4Unverified
8LiteFlowNet3-SAverage End-Point Error1.3Unverified
9LiteFlowNet3Average End-Point Error1.3Unverified
10MaskFlownetAverage End-Point Error1.1Unverified
#ModelMetricClaimedVerifiedStatus
1PWCNet1px total82.27Unverified
2SPyNet1px total29.96Unverified
3GMFlow1px total10.36Unverified
4GMA1px total7.07Unverified
5RAFT1px total6.79Unverified
6FlowNet21px total6.71Unverified
7FlowFormer1px total6.51Unverified
8MS-RAFT+1px total5.72Unverified
9RPKNet1px total4.81Unverified
10DPFlow1px total3.44Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error5.21Unverified
2MDFlow-FastAverage End-Point Error4.73Unverified
3UpFlowAverage End-Point Error4.68Unverified
4ARFlow-MVAverage End-Point Error4.49Unverified
5MDFlowAverage End-Point Error4.16Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error6.5Unverified
2MDFlow-FastAverage End-Point Error5.99Unverified
3ARFlow-MVAverage End-Point Error5.67Unverified
4MDFlowAverage End-Point Error5.46Unverified
5UpFlowAverage End-Point Error5.32Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVFl-all11.79Unverified
2MDFlow-FastFl-all11.43Unverified
3UpFlowFl-all9.38Unverified
4MDFlowFl-all8.91Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVAverage End-Point Error1.5Unverified
2UpFlowAverage End-Point Error1.4Unverified