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 19512000 of 2184 papers

TitleStatusHype
Attacking Optical FlowCode0
CloudCast: A Satellite-Based Dataset and Baseline for Forecasting CloudsCode0
STEPs: Self-Supervised Key Step Extraction and Localization from Unlabeled Procedural VideosCode0
FlowGrad: Using Motion for Visual Sound Source LocalizationCode0
CardioSpectrum: Comprehensive Myocardium Motion Analysis with 3D Deep Learning and Geometric InsightsCode0
Low-light Environment Neural SurveillanceCode0
Triple-level Model Inferred Collaborative Network Architecture for Video DerainingCode0
NOVA: NOvel View Augmentation for Neural Composition of Dynamic ObjectsCode0
A torus model for optical flowCode0
A Framework for Event-based Computer Vision on a Mobile DeviceCode0
Long-term Temporal Convolutions for Action RecognitionCode0
First image then video: A two-stage network for spatiotemporal video denoisingCode0
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video ArchitecturesCode0
Filter Flow Made Practical: Massively Parallel and Lock-FreeCode0
FG-DFPN: Flow Guided Deformable Frame Prediction NetworkCode0
RomniStereo: Recurrent Omnidirectional Stereo MatchingCode0
Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuliCode0
A Deep Neural Framework for Continuous Sign Language Recognition by Iterative TrainingCode0
S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural NetworksCode0
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action DetectionCode0
Features Understanding in 3D CNNs for Actions Recognition in VideoCode0
Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action RecognitionCode0
Deep Video InpaintingCode0
Deep Video Frame Interpolation using Cyclic Frame GenerationCode0
DeepV2D: Video to Depth with Differentiable Structure from MotionCode0
Fast, Robust, Continuous Monocular Egomotion ComputationCode0
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow EstimationCode0
SAILenv: Learning in Virtual Visual Environments Made SimpleCode0
Occlusion Guided Scene Flow Estimation on 3D Point CloudsCode0
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule RoutingCode0
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow EstimationCode0
Using phase instead of optical flow for action recognitionCode0
FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of DiffeomorphismsCode0
Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual OdometryCode0
Using Visual Anomaly Detection for Task Execution MonitoringCode0
SAM-Based Building Change Detection with Distribution-Aware Fourier Adaptation and Edge-Constrained WarpingCode0
Two-Stream AMTnet for Action DetectionCode0
Sublabel-Accurate Convex Relaxation of Vectorial Multilabel EnergiesCode0
Subtle Signals: Video-based Detection of Infant Non-nutritive Sucking as a Neurodevelopmental CueCode0
UVid-Net: Enhanced Semantic Segmentation of UAV Aerial Videos by Embedding Temporal InformationCode0
Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression RecognitionCode0
Two-Stream Convolutional Networks for Action Recognition in VideosCode0
Fast Feature Extraction with CNNs with Pooling LayersCode0
Let's Dance: Learning From Online Dance VideosCode0
Online Unsupervised Video Object Segmentation via Contrastive Motion ClusteringCode0
FALDOI: A new minimization strategy for large displacement variational optical flowCode0
Learning to Steer by Mimicking Features from Heterogeneous Auxiliary NetworksCode0
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video InterpolationCode0
Deep Segmentation and Registration in X-Ray Angiography VideoCode0
Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark DetectorsCode0
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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