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 14511500 of 2184 papers

TitleStatusHype
Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition0
Ego-motion and Surrounding Vehicle State Estimation Using a Monocular Camera0
Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction0
Fast Convex Relaxations using Graph Discretizations0
How Do Neural Networks Estimate Optical Flow? A Neuropsychology-Inspired Study0
Music Gesture for Visual Sound Separation0
LSM: Learning Subspace Minimization for Low-level Vision0
End-to-End Learning for Video Frame Compression with Self-Attention0
Visual Descriptor Learning from Monocular Video0
Self-Supervised training for blind multi-frame video denoising0
Optical Flow Estimation in the Deep Learning Age0
Optical Flow in Dense Foggy Scenes using Semi-Supervised Learning0
Two-Stream AMTnet for Action DetectionCode0
Single Image Optical Flow Estimation with an Event Camera0
Autonomous Apex Detection and Micro-Expression Recognition using Proposed Diagonal Planes0
Distance Surface for Event-Based Optical Flow0
Video-based Person Re-Identification using Gated Convolutional Recurrent Neural Networks0
Fully Automated Hand Hygiene Monitoring\ Operating Room using 3D Convolutional Neural Network0
Probabilistic Future Prediction for Video Scene Understanding0
Understanding Crowd Flow Movements Using Active-Langevin Model0
FlowFusion: Dynamic Dense RGB-D SLAM Based on Optical Flow0
Group Activity Recognition by Using Effective Multiple Modality Relation Representation With Temporal-Spatial Attention0
Restore from Restored: Video Restoration with Pseudo Clean Video0
DFVS: Deep Flow Guided Scene Agnostic Image Based Visual Servoing0
Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVsCode0
STC-Flow: Spatio-temporal Context-aware Optical Flow Estimation0
Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization0
Feasibility of Video-based Sub-meter Localization on Resource-constrained Platforms0
Human Action Recognition using Local Two-Stream Convolution Neural Network Features and Support Vector Machines0
Self-Supervised Object-in-Gripper Segmentation from Robotic Motions0
Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition0
Predictive online optimisation with applications to optical flowCode0
Differentiable Forward and Backward Fixed-Point Iteration Layers0
Depth Map Estimation of Dynamic Scenes Using Prior Depth Information0
Modality Compensation Network: Cross-Modal Adaptation for Action Recognition0
Removing Multi-frame Gaussian Noise by Combining Patch-based Filters with Optical Flow0
The benefits of synthetic data for action categorization0
FPCR-Net: Feature Pyramidal Correlation and Residual Reconstruction for Optical Flow Estimation0
Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors0
Subjective Annotation for a Frame Interpolation Benchmark using Artefact Amplification0
Aggressive Perception-Aware Navigation using Deep Optical Flow Dynamics and PixelMPC0
AD-VO: Scale-Resilient Visual Odometry Using Attentive Disparity Map0
First image then video: A two-stage network for spatiotemporal video denoisingCode0
Video Depth Estimation by Fusing Flow-to-Depth ProposalsCode0
Efficient Video Semantic Segmentation with Labels Propagation and Refinement0
Depth Extraction from Video Using Non-parametric Sampling0
DepthTransfer: Depth Extraction from Video Using Non-parametric Sampling0
Improving Optical Flow on a Pyramid Level0
ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization0
Evolution of Robust High Speed Optical-Flow-Based Landing for Autonomous MAVs0
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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