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 751–800 of 2184 papers

TitleStatusHype
GlobalFlowNet: Video Stabilization using Deep Distilled Global Motion EstimatesCode1
Real-time AdaBoost cascade face tracker based on likelihood map and optical flow—0
CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation—0
Attacking Motion Estimation with Adversarial Snow—0
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View CompletionCode2
Spatio-Temporal-based Context Fusion for Video Anomaly Detection—0
A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution—0
LAD: A Hybrid Deep Learning System for Benign Paroxysmal Positional Vertigo Disorders Diagnostic—0
Real-time Action Recognition for Fine-Grained Actions and The Hand Wash DatasetCode0
PSNet: Parallel Symmetric Network for Video Salient Object Detection—0
Masked Motion Encoding for Self-Supervised Video Representation LearningCode1
Oflib: Facilitating Operations with and on Optical Flow Fields in PythonCode1
Weakly-Supervised Optical Flow Estimation for Time-of-FlightCode0
Facial Expression Spotting Based on Optical Flow FeaturesCode0
Micro Expression Generation with Thin-plate Spline Motion Model and Face ParsingCode1
DeepHS-HDRVideo: Deep High Speed High Dynamic Range Video Reconstruction—0
Students taught by multimodal teachers are superior action recognizers—0
Visual Looming from Motion Field and Surface Normals—0
Self-Aligned Concave Curve: Illumination Enhancement for Unsupervised Adaptation—0
Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter VideoCode1
Event-based Temporally Dense Optical Flow Estimation with Sequential LearningCode1
WorldGen: A Large Scale Generative Simulator—0
Motion-inductive Self-supervised Object Discovery in Videos—0
Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications—0
RALACs: Action Recognition in Autonomous Vehicles using Interaction Encoding and Optical FlowCode0
Spatio-Temporal Relation Learning for Video Anomaly Detection—0
3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion—0
Spatiotemporal Multi-scale Bilateral Motion Network for Gait Recognition—0
Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics—0
E-VFIA : Event-Based Video Frame Interpolation with AttentionCode1
SF2SE3: Clustering Scene Flow into SE(3)-Motions via Proposal and SelectionCode1
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving VideosCode1
NanoFlowNet: Real-time Dense Optical Flow on a Nano Quadcopter—0
INV-Flow2PoseNet: Light-Resistant Rigid Object Pose from Optical Flow of RGB-D Images using Images, Normals and Vertices—0
EDeNN: Event Decay Neural Networks for low latency vision—0
Unsupervised Video Object Segmentation via Prototype Memory NetworkCode1
Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object SegmentationCode1
An Empirical Study of End-to-End Video-Language Transformers with Masked Visual ModelingCode1
Temporal Flow Mask Attention for Open-Set Long-Tailed Recognition of Wild Animals in Camera-Trap Images—0
Stabilize, Decompose, and Denoise: Self-Supervised Fluoroscopy Denoising—0
TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained VideosCode0
User-Controllable Latent Transformer for StyleGAN Image Layout EditingCode2
A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation—0
Learning Task-Oriented Flows to Mutually Guide Feature Alignment in Synthesized and Real Video Denoising—0
ICANet: A Method of Short Video Emotion Recognition Driven by Multimodal Data—0
Motion Robust High-Speed Light-Weighted Object Detection With Event CameraCode1
Unsupervised Fish Trajectory Tracking and Segmentation—0
Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow—0
Learning Omnidirectional Flow in 360-degree Video via Siamese Representation—0
Exploring Long- and Short-Range Temporal Information for Learned Video CompressionCode0
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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