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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–900 of 2184 papers

TitleStatusHype
Motion Estimation for Large Displacements and Deformations—0
A Simple Baseline for Video Restoration with Grouped Spatial-temporal ShiftCode1
Optical Flow Regularization of Implicit Neural Representations for Video Frame Interpolation—0
Learning to Estimate and Refine Fluid Motion with Physical DynamicsCode1
HairFIT: Pose-Invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-Region-Aware Inpainting—0
Enhanced Bi-directional Motion Estimation for Video Frame InterpolationCode1
Colonoscopy 3D Video Dataset with Paired Depth from 2D-3D Registration—0
GradICON: Approximate Diffeomorphisms via Gradient Inverse ConsistencyCode1
Audio-video fusion strategies for active speaker detection in meetings—0
GateHUB: Gated History Unit with Background Suppression for Online Action Detection—0
Unsupervised Learning of 3D Scene Flow from Monocular CameraCode0
TadML: A fast temporal action detection with Mechanics-MLPCode0
Physically Inspired Constraint for Unsupervised Regularized Ultrasound Elastography—0
3D Convolutional with Attention for Action Recognition—0
Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2021—0
MSTCGAN: Multiscale time conditional generative adversarial network for long-term satellite image sequence predictionCode0
Sign Language Video Anonymization—0
IFRNet: Intermediate Feature Refine Network for Efficient Frame InterpolationCode2
Feature-Aligned Video Raindrop Removal with Temporal Constraints—0
SKFlow: Learning Optical Flow with Super KernelsCode1
DeepRM: Deep Recurrent Matching for 6D Pose Refinement—0
FlowNet-PET: Unsupervised Learning to Perform Respiratory Motion Correction in PET ImagingCode0
Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video RestorationCode1
Unsupervised Learning of Depth, Camera Pose and Optical Flow from Monocular Video—0
Unsupervised Segmentation in Real-World Images via Spelke Object InferenceCode1
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion—0
A Framework for Event-based Computer Vision on a Mobile DeviceCode0
Dynamic Dense RGB-D SLAM using Learning-based Visual Odometry—0
Data-Driven Optimal Sensor Placement for High-Dimensional System Using Annealing Machine—0
Multiview Stereo with Cascaded Epipolar RAFTCode1
EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms—0
Handcrafted localized phase features for human action recognition—0
Exploiting Correspondences with All-pairs Correlations for Multi-view Depth Estimation—0
Object Class Aware Video Anomaly Detection through Image Translation—0
GeoRefine: Self-Supervised Online Depth Refinement for Accurate Dense Mapping—0
RAFT-MSF: Self-Supervised Monocular Scene Flow using Recurrent Optimizer—0
D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion PredictionCode1
Emotion-Controllable Generalized Talking Face Generation—0
ClothFormer:Taming Video Virtual Try-on in All ModuleCode1
Video Frame Interpolation Based on Deformable Kernel RegionCode0
A New Dataset and Transformer for Stereoscopic Video Super-ResolutionCode1
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition—0
A qualitative investigation of optical flow algorithms for video denoising—0
Deep Equilibrium Optical Flow EstimationCode1
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable AlignmentCode1
Lagrangian Motion Magnification with Double Sparse Optical Flow DecompositionCode0
Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference ModelingCode1
Autonomous Satellite Detection and Tracking using Optical Flow—0
Imposing Consistency for Optical Flow Estimation—0
Event TransformerCode0
Show:102550
← PrevPage 18 of 44Next →
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
4LiteFlowNet-ftAverage End-Point Error5.38—Unverified
5MR-FlowAverage 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
2IRR-PWCAverage End-Point Error1.6—Unverified
3LiteFlowNet-ftAverage End-Point Error1.6—Unverified
4PWC-Net + ft - axXivAverage End-Point Error1.5—Unverified
5FDFlowNet-ftAverage End-Point Error1.5—Unverified
6SelFlowAverage End-Point Error1.5—Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4—Unverified
8LiteFlowNet3Average End-Point Error1.3—Unverified
9LiteFlowNet3-SAverage End-Point Error1.3—Unverified
10MaskFlownet-SAverage 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