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 51–100 of 2184 papers

TitleStatusHype
MicroFlow: Domain-Specific Optical Flow for Ground Deformation Estimation in Seismic Events—0
Neural Ganglion Sensors: Learning Task-specific Event Cameras Inspired by the Neural Circuit of the Human Retina—0
SAM-Based Building Change Detection with Distribution-Aware Fourier Adaptation and Edge-Constrained WarpingCode0
Event-Enhanced Blurry Video Super-ResolutionCode3
SC3EF: A Joint Self-Correlation and Cross-Correspondence Estimation Framework for Visible and Thermal Image Registration—0
Perturbed State Space Feature Encoders for Optical Flow with Event Cameras—0
WildLive: Near Real-time Visual Wildlife Tracking onboard UAVs—0
Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: a Review—0
ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object SegmentationCode0
Extending Visual Dynamics for Video-to-Music Generation—0
Saliency-Motion Guided Trunk-Collateral Network for Unsupervised Video Object Segmentation—0
Towards Efficient Real-Time Video Motion Transfer via Generative Time Series Modeling—0
FluentLip: A Phonemes-Based Two-stage Approach for Audio-Driven Lip Synthesis with Optical Flow Consistency—0
Simultaneous Motion And Noise Estimation with Event CamerasCode0
Easi3R: Estimating Disentangled Motion from DUSt3R Without TrainingCode4
ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation with Zero-Shot MethodCode0
Towards Mobile Sensing with Event Cameras on High-agility Resource-constrained Devices: A Survey—0
Synergistic Bleeding Region and Point Detection in Surgical Videos—0
Segment Any Motion in Videos—0
Endo-TTAP: Robust Endoscopic Tissue Tracking via Multi-Facet Guided Attention and Hybrid Flow-point Supervision—0
Can Video Diffusion Model Reconstruct 4D Geometry?—0
VADMamba: Exploring State Space Models for Fast Video Anomaly DetectionCode1
Burst Image Super-Resolution with Mamba—0
NexusGS: Sparse View Synthesis with Epipolar Depth Priors in 3D Gaussian Splatting—0
MotionDiff: Training-free Zero-shot Interactive Motion Editing via Flow-assisted Multi-view Diffusion—0
Generating, Fast and Slow: Scalable Parallel Video Generation with Video Interface Networks—0
Unsupervised Joint Learning of Optical Flow and Intensity with Event CamerasCode1
4D Gaussian Splatting SLAM—0
EDEN: Enhanced Diffusion for High-quality Large-motion Video Frame InterpolationCode2
Temporal-Consistent Video Restoration with Pre-trained Diffusion Models—0
DPFlow: Adaptive Optical Flow Estimation with a Dual-Pyramid FrameworkCode4
GeoFlow-SLAM: A Robust Tightly-Coupled RGBD-Inertial Fusion SLAM for Dynamic Legged RoboticsCode0
UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural NetworksCode1
Zero-TIG: Temporal Consistency-Aware Zero-Shot Illumination-Guided Low-light Video EnhancementCode0
EMoTive: Event-guided Trajectory Modeling for 3D Motion Estimation—0
FG-DFPN: Flow Guided Deformable Frame Prediction NetworkCode0
Flow-NeRF: Joint Learning of Geometry, Poses, and Dense Flow within Unified Neural Representations—0
Markerless Tracking-Based Registration for Medical Image Motion Correction—0
ST-FlowNet: An Efficient Spiking Neural Network for Event-Based Optical Flow Estimation—0
Investigation of Frame Differences as Motion Cues for Video Object Segmentation—0
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—0
MambaFlow: A Mamba-Centric Architecture for End-to-End Optical Flow Estimation—0
Bridge Frame and Event: Common Spatiotemporal Fusion for High-Dynamic Scene Optical Flow—0
Online Dense Point Tracking with Streaming MemoryCode1
Stereo Any Video: Temporally Consistent Stereo Matching—0
VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context ControlCode4
ReynoldsFlow: Exquisite Flow Estimation via Reynolds Transport TheoremCode0
BAT: Learning Event-based Optical Flow with Bidirectional Adaptive Temporal CorrelationCode0
Anomaly detection in non-stationary videos using time-recursive differencing network based prediction—0
AI-Driven Relocation Tracking in Dynamic Kitchen EnvironmentsCode0
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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
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