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 20512100 of 2184 papers

TitleStatusHype
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven PoolingCode0
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel EnergiesCode0
Exploiting Semantic Information and Deep Matching for Optical Flow0
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos0
Video Interpolation using Optical Flow and Laplacian Smoothness0
Nonrigid Optical Flow Ground Truth for Real-World Scenes with Time-Varying Shading Effects0
Position and Vector Detection of Blind Spot motion with the Horn-Schunck Optical Flow0
Illumination-invariant image mosaic calculation based on logarithmic search0
Pushing the Limits of Deep CNNs for Pedestrian Detection0
Dynamic Scene Deblurring using a Locally Adaptive Linear Blur Model0
Optical Flow with Semantic Segmentation and Localized Layers0
Fast Optical Flow using Dense Inverse Search0
Drift Robust Non-rigid Optical Flow Enhancement for Long Sequences0
Blur Robust Optical Flow using Motion Channel0
Automatic learning of gait signatures for people identification0
FALDOI: A new minimization strategy for large displacement variational optical flowCode0
Fast, Robust, Continuous Monocular Egomotion ComputationCode0
A diffusion and clustering-based approach for finding coherent motions and understanding crowd scenes0
A Semi-Automated Method for Object Segmentation in Infant's Egocentric Videos to Study Object Perception0
Learning to Extract Motion from Videos in Convolutional Neural Networks0
Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization0
Unsupervised convolutional neural networks for motion estimation0
Sparse Coding with Fast Image Alignment via Large Displacement Optical Flow0
Origami: A 803 GOp/s/W Convolutional Network Accelerator0
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow EstimationCode1
PatchBatch: a Batch Augmented Loss for Optical Flow0
Intrinsic Depth: Improving Depth Transfer With Intrinsic Images0
Large Displacement 3D Scene Flow With Occlusion Reasoning0
SpeDo: 6 DOF Ego-Motion Sensor Using Speckle Defocus Imaging0
Oriented Light-Field Windows for Scene Flow0
SPM-BP: Sped-up PatchMatch Belief Propagation for Continuous MRFs0
Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment0
Face Flow0
Mutual-Structure for Joint Filtering0
Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing0
Unsupervised Tube Extraction Using Transductive Learning and Dense TrajectoriesCode0
Direct, Dense, and Deformable: Template-Based Non-Rigid 3D Reconstruction From RGB Video0
Photogeometric Scene Flow for High-Detail Dynamic 3D Reconstruction0
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution0
On Optical Flow Models for Variational Motion Estimation0
Deep End2End Voxel2Voxel Prediction0
Personalizing Human Video Pose Estimation0
Spatio-temporal video autoencoder with differentiable memoryCode0
Deep multi-scale video prediction beyond mean square errorCode0
Handcrafted Local Features are Convolutional Neural Networks0
Coherent Motion Segmentation in Moving Camera Videos using Optical Flow Orientations0
Enhancing Feature Tracking With Gyro Regularization0
Bregman Iteration for Correspondence Problems: A Study of Optical Flow0
A Dual Fast and Slow Feature Interaction in Biologically Inspired Visual Recognition of Human Action0
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation0
Show:102550
← PrevPage 42 of 44Next →

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