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

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Showing 301–350 of 2184 papers

TitleStatusHype
Learning RAW-to-sRGB Mappings with Inaccurately Aligned SupervisionCode1
Learning Single Image Defocus Deblurring with Misaligned Training PairsCode1
Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo VideosCode1
Deep Equilibrium Optical Flow EstimationCode1
Deep Video Matting via Spatio-Temporal Alignment and AggregationCode1
DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-ReflectorsCode1
Texture-guided Saliency Distilling for Unsupervised Salient Object DetectionCode1
Displacement-Invariant Matching Cost Learning for Accurate Optical Flow EstimationCode1
Distracting Downpour: Adversarial Weather Attacks for Motion EstimationCode1
Comparing Correspondences: Video Prediction with Correspondence-wise LossesCode1
IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D ReconstructionCode1
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost VolumeCode1
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B ImageryCode1
Less is More: Consistent Video Depth Estimation with Masked Frames ModelingCode1
Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow EstimationCode1
DS-Net: Dynamic Spatiotemporal Network for Video Salient Object DetectionCode1
LightedDepth: Video Depth Estimation in Light of Limited Inference View AnglesCode1
Lightweight Event-based Optical Flow Estimation via Iterative DeblurringCode1
Learning Motion-Robust Remote Photoplethysmography through Arbitrary Resolution VideosCode1
D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion PredictionCode1
Conditional Object-Centric Learning from VideoCode1
Interactive Control over Temporal Consistency while Stylizing Video StreamsCode1
AnimeRun: 2D Animation Visual Correspondence from Open Source 3D MoviesCode1
Edge-guided Multi-domain RGB-to-TIR image Translation for Training Vision Tasks with Challenging LabelsCode1
Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical VideoCode1
EVLoc: Event-based Visual Localization in LiDAR Maps via Event-Depth RegistrationCode1
CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow EstimationCode1
Volterra Neural Networks (VNNs)Code1
Conquering the cnn over-parameterization dilemma: A volterra filtering approach for action recognitionCode1
Efficient Video Deblurring Guided by Motion MagnitudeCode1
Decoupling Dynamic Monocular Videos for Dynamic View SynthesisCode1
EM-driven unsupervised learning for efficient motion segmentationCode1
End-to-end Learning for Inter-Vehicle Distance and Relative Velocity Estimation in ADAS with a Monocular CameraCode1
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
Internal Video Inpainting by Implicit Long-range PropagationCode1
Entropy Minimisation Framework for Event-based Vision Model EstimationCode1
A Simple Detector with Frame Dynamics is a Strong TrackerCode1
Enhanced Bi-directional Motion Estimation for Video Frame InterpolationCode1
Unified Domain Adaptive Semantic SegmentationCode1
Estimating People Flows to Better Count Them in Crowded ScenesCode1
Event-based Background-Oriented SchlierenCode1
Memory-augmented Dense Predictive Coding for Video Representation LearningCode1
Event Collapse in Contrast Maximization FrameworksCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Animation from Blur: Multi-modal Blur Decomposition with Motion GuidanceCode1
BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical FlowCode1
COTR: Correspondence Transformer for Matching Across ImagesCode1
Counting People by Estimating People FlowsCode1
Mining Negative Temporal Contexts For False Positive Suppression In Real-Time Ultrasound Lesion DetectionCode1
Deep Animation Video Interpolation in the WildCode1
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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
4MR-FlowAverage End-Point Error5.38—Unverified
5LiteFlowNet-ftAverage 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
2LiteFlowNet-ftAverage End-Point Error1.6—Unverified
3IRR-PWCAverage End-Point Error1.6—Unverified
4SelFlowAverage End-Point Error1.5—Unverified
5FDFlowNet-ftAverage End-Point Error1.5—Unverified
6PWC-Net + ft - axXivAverage End-Point Error1.5—Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4—Unverified
8LiteFlowNet3-SAverage End-Point Error1.3—Unverified
9LiteFlowNet3Average End-Point Error1.3—Unverified
10MaskFlownetAverage 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