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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 151–200 of 2184 papers

TitleStatusHype
Chasing Day and Night: Towards Robust and Efficient All-Day Object Detection Guided by an Event CameraCode1
MPI-Flow: Learning Realistic Optical Flow with Multiplane ImagesCode1
Dynamic Frame Interpolation in Wavelet DomainCode1
AccFlow: Backward Accumulation for Long-Range Optical FlowCode1
LAN-HDR: Luminance-based Alignment Network for High Dynamic Range Video ReconstructionCode1
MGMAE: Motion Guided Masking for Video Masked AutoencodingCode1
FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous DrivingCode1
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost VolumeCode1
Versatile Face Animator: Driving Arbitrary 3D Facial Avatar in RGBD SpaceCode1
StableVQA: A Deep No-Reference Quality Assessment Model for Video StabilityCode1
BubbleML: A Multi-Physics Dataset and Benchmarks for Machine LearningCode1
Optical Flow boosts Unsupervised Localization and SegmentationCode1
Fast Full-frame Video Stabilization with Iterative OptimizationCode1
Automatic Infant Respiration Estimation from Video: A Deep Flow-based Algorithm and a Novel Public BenchmarkCode1
Deficiency-Aware Masked Transformer for Video InpaintingCode1
Multimodal Distillation for Egocentric Action RecognitionCode1
Towards Anytime Optical Flow Estimation with Event CamerasCode1
The Drunkard's Odometry: Estimating Camera Motion in Deforming ScenesCode1
Delving into Crispness: Guided Label Refinement for Crisp Edge DetectionCode1
Shape-Constraint Recurrent Flow for 6D Object Pose EstimationCode1
SplatFlow: Learning Multi-frame Optical Flow via SplattingCode1
MMASD: A Multimodal Dataset for Autism Intervention AnalysisCode1
Mining Negative Temporal Contexts For False Positive Suppression In Real-Time Ultrasound Lesion DetectionCode1
Distracting Downpour: Adversarial Weather Attacks for Motion EstimationCode1
FlowText: Synthesizing Realistic Scene Text Video with Optical Flow EstimationCode1
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
Learning How To Robustly Estimate Camera Pose in Endoscopic VideosCode1
Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual GroupingCode1
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B ImageryCode1
Soundini: Sound-Guided Diffusion for Natural Video EditingCode1
Local-Global Temporal Difference Learning for Satellite Video Super-ResolutionCode1
DEFLOW: Self-supervised 3D Motion Estimation of Debris FlowCode1
MMVC: Learned Multi-Mode Video Compression with Block-based Prediction Mode Selection and Density-Adaptive Entropy CodingCode1
Decoupling Dynamic Monocular Videos for Dynamic View SynthesisCode1
VIVE3D: Viewpoint-Independent Video Editing using 3D-Aware GANsCode1
TimeBalance: Temporally-Invariant and Temporally-Distinctive Video Representations for Semi-Supervised Action RecognitionCode1
TMA: Temporal Motion Aggregation for Event-based Optical FlowCode1
Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationCode1
Rethinking Optical Flow from Geometric Matching Consistent PerspectiveCode1
Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency LossesCode1
SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous DrivingCode1
Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and StereoCode1
FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow EstimationCode1
Neural Video Compression with Diverse ContextsCode1
Deep Learning for Event-based Vision: A Comprehensive Survey and BenchmarksCode1
Optical flow estimation from event-based cameras and spiking neural networksCode1
SurgT challenge: Benchmark of Soft-Tissue Trackers for Robotic SurgeryCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Edge-guided Multi-domain RGB-to-TIR image Translation for Training Vision Tasks with Challenging LabelsCode1
Mono-STAR: Mono-camera Scene-level Tracking and ReconstructionCode1
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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