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 18011850 of 2184 papers

TitleStatusHype
Recognize Actions by Disentangling Components of Dynamics0
PoseFlow: A Deep Motion Representation for Understanding Human Behaviors in Videos0
Simultaneous Optical Flow and Segmentation (SOFAS) using Dynamic Vision Sensor0
Novel Video Prediction for Large-scale Scene using Optical Flow0
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion SegmentationCode0
A Convolutional Feature Map based Deep Network targeted towards Traffic Detection and Classification0
VideoCapsuleNet: A Simplified Network for Action Detection0
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow EstimationCode0
Joint direct estimation of 3D geometry and 3D motion using spatio temporal gradients0
Deep Segmentation and Registration in X-Ray Angiography VideoCode0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning0
ABMOF: A Novel Optical Flow Algorithm for Dynamic Vision Sensors0
OFF-ApexNet on Micro-expression Recognition System0
FlowFields++: Accurate Optical Flow Correspondences Meet Robust Interpolation0
Layered Optical Flow Estimation Using a Deep Neural Network with a Soft Mask0
Learning on the Edge: Explicit Boundary Handling in CNNsCode0
Fast Feature Extraction with CNNs with Pooling LayersCode0
Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network0
Learning Optical Flow via Dilated Networks and Occlusion Reasoning0
A Numerical Framework for Efficient Motion Estimation on Evolving Sphere-Like Surfaces based on Brightness and Mass Conservation LawsCode0
Object Tracking in Satellite Videos Based on a Multi-Frame Optical Flow Tracker0
Cubes3D: Neural Network based Optical Flow in Omnidirectional Image ScenesCode0
Superframes, A Temporal Video Segmentation0
Temporal Unknown Incremental Clustering (TUIC) Model for Analysis of Traffic Surveillance Videos0
Mutual Suppression Network for Video Prediction using Disentangled Features0
Deep Motion Boundary Detection0
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field EstimationCode0
Multi-Scale Generalized Plane Match for Optical Flow0
A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow EstimationCode0
Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms0
End-to-End Learning of Motion Representation for Video UnderstandingCode0
Predicting Future Instance Segmentation by Forecasting Convolutional FeaturesCode0
Context-aware Synthesis for Video Frame Interpolation0
Stochastic Variational Inference with Gradient Linearization0
CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF0
Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation0
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences0
Queuing Theory Guided Intelligent Traffic Scheduling through Video Analysis using Dirichlet Process Mixture Model0
Object Detection in Video with Spatiotemporal Sampling Networks0
Event-based Moving Object Detection and Tracking0
Tracking of the Internal Jugular Vein in Ultrasound Images Using Optical Flow0
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera PoseCode0
A Feature Clustering Approach Based on Histogram of Oriented Optical Flow and Superpixels0
ReHAR: Robust and Efficient Human Activity Recognition0
Real-Time End-to-End Action Detection with Two-Stream Networks0
Devon: Deformable Volume Network for Learning Optical Flow0
Camera-based vehicle velocity estimation from monocular video0
Uncertainty Estimates and Multi-Hypotheses Networks for Optical FlowCode0
Correlation Flow: Robust Optical Flow Using Kernel Cross-CorrelatorsCode0
EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based CamerasCode0
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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
4LiteFlowNet-ftAverage End-Point Error5.38Unverified
5MR-FlowAverage 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
2IRR-PWCAverage End-Point Error1.6Unverified
3LiteFlowNet-ftAverage End-Point Error1.6Unverified
4PWC-Net + ft - axXivAverage End-Point Error1.5Unverified
5FDFlowNet-ftAverage End-Point Error1.5Unverified
6SelFlowAverage End-Point Error1.5Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4Unverified
8LiteFlowNet3Average End-Point Error1.3Unverified
9LiteFlowNet3-SAverage End-Point Error1.3Unverified
10MaskFlownet-SAverage 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