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 1051–1100 of 2184 papers

TitleStatusHype
What happens in Face during a facial expression? Using data mining techniques to analyze facial expression motion vectors—0
Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural NetworkCode0
Temporally Coherent Person Matting Trained on Fake-Motion Dataset—0
Automatic Portrait Video Matting via Context Motion Network—0
Spatio-Temporal Recurrent Networks for Event-Based Optical Flow EstimationCode1
SlowFast Rolling-Unrolling LSTMs for Action Anticipation in Egocentric Videos—0
Learning to Track Objects from Unlabeled VideosCode1
A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data—0
Learning Cross-modal Contrastive Features for Video Domain Adaptation—0
Full-Velocity Radar Returns by Radar-Camera Fusion—0
E-RAFT: Dense Optical Flow from Event CamerasCode1
Out-of-boundary View Synthesis Towards Full-Frame Video StabilizationCode1
MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition—0
Learning RAW-to-sRGB Mappings with Inaccurately Aligned SupervisionCode1
Diffeomorphic Particle Image VelocimetryCode1
Adaptive Semantic-Spatio-Temporal Graph Convolutional Network for Lip Reading—0
A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame PredictionCode1
EventHPE: Event-based 3D Human Pose and Shape EstimationCode1
An optical flow approach to tracking ship track behavior using GOES-R satellite imagery—0
Deep Motion Prior for Weakly-Supervised Temporal Action Localization—0
Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos—0
Feature-Supervised Action Modality Transfer—0
End-to-end Neural Video Coding Using a Compound Spatiotemporal Representation—0
Video Abnormal Event Detection by Learning to Complete Visual Cloze TestsCode1
Internal Video Inpainting by Implicit Long-range PropagationCode1
Wavelet-Based Network For High Dynamic Range ImagingCode1
Neural Image Representations for Multi-Image Fusion and Layer Separation—0
Perceiver IO: A General Architecture for Structured Inputs & OutputsCode1
Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognition—0
Temporal Feature Warping for Video Shadow Detection—0
Using Visual Anomaly Detection for Task Execution MonitoringCode0
Spot What Matters: Learning Context Using Graph Convolutional Networks for Weakly-Supervised Action DetectionCode1
Detail Preserving Residual Feature Pyramid Modules for Optical Flow—0
Deep Iterative 2D/3D Registration—0
LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance ImagingCode0
Progressive Deep Video Dehazing without Explicit Alignment Estimation—0
CCVS: Context-aware Controllable Video SynthesisCode1
MeNToS: Tracklets Association with a Space-Time Memory Network—0
DDCNet-Multires: Effective Receptive Field Guided Multiresolution CNN for Dense Prediction—0
End-to-end Multi-modal Video Temporal GroundingCode1
BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving—0
DDCNet: Deep Dilated Convolutional Neural Network for Dense Prediction—0
RGB Stream Is Enough for Temporal Action DetectionCode1
NccFlow: Unsupervised Learning of Optical Flow With Non-occlusion from Geometry—0
Plot2Spectra: an Automatic Spectra Extraction ToolCode1
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information—0
SDOF-Tracker: Fast and Accurate Multiple Human Tracking by Skipped-Detection and Optical-FlowCode0
Class agnostic moving target detection by color and location prediction of moving area—0
MODETR: Moving Object Detection with Transformers—0
Temporal Early Exits for Efficient Video Object Detection—0
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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