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 17511800 of 2184 papers

TitleStatusHype
DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task ConsistencyCode0
Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation0
Optical Flow Super-Resolution Based on Image Guidence Using Convolutional Neural Network0
3D Vehicle Trajectory Reconstruction in Monocular Video Data Using Environment Structure Constraints0
Selfie Video Stabilization0
SDC-Net: Video prediction using spatially-displaced convolutionCode0
Structure-from-Motion-Aware PatchMatch for Adaptive Optical Flow Estimation0
3D Scene Flow from 4D Light Field Gradients0
Robust Optical Flow in Rainy Scenes0
Simultaneous 3D Reconstruction for Water Surface and Underwater Scene0
A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding0
Spatio-temporal Transformer Network for Video Restoration0
MRF Optimization with Separable Convex Prior on Partially Ordered Labels0
Unsupervised Learning of Multi-Frame Optical Flow with Occlusions0
Dense Scene Flow from Stereo Disparity and Optical Flow0
Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous Vehicles0
AAD: Adaptive Anomaly Detection through traffic surveillance videos0
Deep Lidar CNN to Understand the Dynamics of Moving Vehicles0
Stereo 3D Object Trajectory Reconstruction0
Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition0
Joint Coarse-And-Fine Reasoning for Deep Optical Flow0
FusionNet and AugmentedFlowNet: Selective Proxy Ground Truth for Training on Unlabeled Images0
Dual approach for object tracking based on optical flow and swarm intelligence0
Deep Transfer Learning for EEG-based Brain Computer Interface0
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow EstimationCode0
Learning Blind Video Temporal ConsistencyCode0
Leveraging Motion Priors in Videos for Improving Human Segmentation0
Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion PerceptionCode0
Conditional Prior Networks for Optical FlowCode0
Motion Feature Network: Fixed Motion Filter for Action Recognition0
Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography0
Three for one and one for three: Flow, Segmentation, and Surface NormalsCode0
Signal Alignment for Humanoid Skeletons via the Globally Optimal Reparameterization Algorithm0
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on VideoCode0
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs0
Cross Pixel Optical Flow Similarity for Self-Supervised Learning0
Optical Flow Based Real-time Moving Object Detection in Unconstrained Scenes0
SymmNet: A Symmetric Convolutional Neural Network for Occlusion Detection0
Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark DetectorsCode0
Multi-modal Egocentric Activity Recognition using Audio-Visual Features0
Action Recognition for Depth Video using Multi-view Dynamic ImagesCode0
Accurate and efficient video de-fencing using convolutional neural networks and temporal informationCode0
Modeling Spatio-Temporal Human Track Structure for Action Localization0
Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D Motion Understanding0
Tracking Emerges by Colorizing VideosCode0
Best Vision Technologies Submission to ActivityNet Challenge 2018-Task: Dense-Captioning Events in Videos0
CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps0
Multimodal feature fusion for CNN-based gait recognition: an empirical comparison0
Task-Relevant Object Discovery and Categorization for Playing First-person Shooter Games0
Real-time Monocular Visual Odometry for Turbid and Dynamic Underwater Environments0
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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