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

Showing 301350 of 2184 papers

TitleStatusHype
Learning Optical Flow With Kernel Patch AttentionCode1
Learning RAW-to-sRGB Mappings with Inaccurately Aligned SupervisionCode1
IVS3D: An Open Source Framework for Intelligent Video Sampling and Preprocessing to Facilitate 3D ReconstructionCode1
DF-VO: What Should Be Learnt for Visual Odometry?Code1
Is Appearance Free Action Recognition Possible?Code1
Joint Unsupervised Learning of Optical Flow and Depth by Watching Stereo VideosCode1
Deep Equilibrium Optical Flow EstimationCode1
Deep Burst Super-ResolutionCode1
Distilled Semantics for Comprehensive Scene Understanding from VideosCode1
Comparing Correspondences: Video Prediction with Correspondence-wise LossesCode1
IPN Hand: A Video Dataset and Benchmark for Real-Time Continuous Hand Gesture RecognitionCode1
Learning Accurate Dense Correspondences and When to Trust ThemCode1
Learning How To Robustly Estimate Camera Pose in Endoscopic VideosCode1
Learning Video Salient Object Detection Progressively from Unlabeled VideosCode1
DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost VolumeCode1
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
DTVNet: Dynamic Time-lapse Video Generation via Single Still ImageCode1
Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the WildCode1
E^2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action RecognitionCode1
D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion PredictionCode1
Conditional Object-Centric Learning from VideoCode1
Infusion: internal diffusion for inpainting of dynamic textures and complex motionCode1
AnimeRun: 2D Animation Visual Correspondence from Open Source 3D MoviesCode1
CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow EstimationCode1
Edge-guided Multi-domain RGB-to-TIR image Translation for Training Vision Tasks with Challenging LabelsCode1
Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference ModelingCode1
Inertia-Guided Flow Completion and Style Fusion for Video InpaintingCode1
Volterra Neural Networks (VNNs)Code1
Conquering the cnn over-parameterization dilemma: A volterra filtering approach for action recognitionCode1
Efficient Semantic Video Segmentation with Per-frame InferenceCode1
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
Unified Domain Adaptive Semantic SegmentationCode1
Event-based Temporally Dense Optical Flow Estimation with Sequential LearningCode1
End-to-end Multi-modal Video Temporal GroundingCode1
A Simple Detector with Frame Dynamics is a Strong TrackerCode1
End-to-End Video Object Detection with Spatial-Temporal TransformersCode1
Animation from Blur: Multi-modal Blur Decomposition with Motion GuidanceCode1
Entropy Minimisation Framework for Event-based Vision Model EstimationCode1
Implicit Motion FunctionCode1
Event-based Background-Oriented SchlierenCode1
BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical FlowCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Event Collapse in Contrast Maximization FrameworksCode1
Decoupling Dynamic Monocular Videos for Dynamic View SynthesisCode1
COTR: Correspondence Transformer for Matching Across ImagesCode1
Counting People by Estimating People FlowsCode1
EventHPE: Event-based 3D Human Pose and Shape EstimationCode1
Interactive Control over Temporal Consistency while Stylizing Video StreamsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error6.64Unverified
2FastFlowNet-ftAverage End-Point Error4.89Unverified
3UnrolledCostAverage End-Point Error4.69Unverified
4LiteFlowNet-ftAverage End-Point Error4.54Unverified
5FlowNet2Average End-Point Error3.96Unverified
6IRR-PWCAverage End-Point Error3.84Unverified
7SelFlowAverage End-Point Error3.74Unverified
8FDFlowNet-ftAverage End-Point Error3.71Unverified
9ScopeFlowAverage End-Point Error3.59Unverified
10LiteFlowNet2-ftAverage End-Point Error3.48Unverified
#ModelMetricClaimedVerifiedStatus
1SpynetAverage End-Point Error8.36Unverified
2FastFlowNet-ftAverage End-Point Error6.08Unverified
3UnrolledCostAverage End-Point Error5.8Unverified
4MR-FlowAverage End-Point Error5.38Unverified
5LiteFlowNet-ftAverage End-Point Error5.38Unverified
6FDFlowNet-ftAverage End-Point Error5.11Unverified
7LiteFlowNet2-ftAverage End-Point Error4.69Unverified
8IRR-PWCAverage End-Point Error4.58Unverified
9LiteFlowNet3-SAverage End-Point Error4.53Unverified
10ContinualFlow + ftAverage End-Point Error4.52Unverified
#ModelMetricClaimedVerifiedStatus
1PWC-NetF1-all33.7Unverified
2FastFlowNetF1-all33.1Unverified
3FlowNet2F1-all30Unverified
4VCNF1-all25.1Unverified
5HD3F1-all24Unverified
6MaskFlowNetF1-all23.1Unverified
7SCVF1-all19.3Unverified
8RAPIDFlowF1-all17.7Unverified
9CRAFTF1-all17.5Unverified
10RAFTF1-all17.4Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftFl-all11.22Unverified
2UnrolledCostFl-all10.81Unverified
3LiteFlowNet-ftFl-all9.38Unverified
4SelFlowFl-all8.42Unverified
5IRR-PWCFl-all7.65Unverified
6LiteFlowNet2-ftFl-all7.62Unverified
7LiteFlowNet3Fl-all7.34Unverified
8LiteFlowNet3-SFl-all7.22Unverified
9MaskFlownet-SFl-all6.81Unverified
10RAPIDFlowFl-all6.12Unverified
#ModelMetricClaimedVerifiedStatus
1FastFlowNet-ftAverage End-Point Error1.8Unverified
2LiteFlowNet-ftAverage End-Point Error1.6Unverified
3IRR-PWCAverage End-Point Error1.6Unverified
4SelFlowAverage End-Point Error1.5Unverified
5FDFlowNet-ftAverage End-Point Error1.5Unverified
6PWC-Net + ft - axXivAverage End-Point Error1.5Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4Unverified
8LiteFlowNet3-SAverage End-Point Error1.3Unverified
9LiteFlowNet3Average End-Point Error1.3Unverified
10MaskFlownetAverage End-Point Error1.1Unverified
#ModelMetricClaimedVerifiedStatus
1PWCNet1px total82.27Unverified
2SPyNet1px total29.96Unverified
3GMFlow1px total10.36Unverified
4GMA1px total7.07Unverified
5RAFT1px total6.79Unverified
6FlowNet21px total6.71Unverified
7FlowFormer1px total6.51Unverified
8MS-RAFT+1px total5.72Unverified
9RPKNet1px total4.81Unverified
10DPFlow1px total3.44Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error5.21Unverified
2MDFlow-FastAverage End-Point Error4.73Unverified
3UpFlowAverage End-Point Error4.68Unverified
4ARFlow-MVAverage End-Point Error4.49Unverified
5MDFlowAverage End-Point Error4.16Unverified
#ModelMetricClaimedVerifiedStatus
1UFlowAverage End-Point Error6.5Unverified
2MDFlow-FastAverage End-Point Error5.99Unverified
3ARFlow-MVAverage End-Point Error5.67Unverified
4MDFlowAverage End-Point Error5.46Unverified
5UpFlowAverage End-Point Error5.32Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVFl-all11.79Unverified
2MDFlow-FastFl-all11.43Unverified
3UpFlowFl-all9.38Unverified
4MDFlowFl-all8.91Unverified
#ModelMetricClaimedVerifiedStatus
1ARFlow-MVAverage End-Point Error1.5Unverified
2UpFlowAverage End-Point Error1.4Unverified