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 1251–1300 of 2184 papers

TitleStatusHype
CNN-based Patch Matching for Optical Flow with Thresholded Hinge Embedding Loss—0
Motion-Augmented Self-Training for Video Recognition at Smaller Scale—0
Motion-aware 3D Gaussian Splatting for Efficient Dynamic Scene Reconstruction—0
Unsupervised Segmentation of Fire and Smoke from Infra-Red Videos—0
Motion-Aware Video Frame Interpolation—0
Motion-blurred Video Interpolation and Extrapolation—0
What's in the Flow? Exploiting Temporal Motion Cues for Unsupervised Generic Event Boundary Detection—0
Motion-Corrected Moving Average: Including Post-Hoc Temporal Information for Improved Video Segmentation—0
CNN-based Action Recognition and Supervised Domain Adaptation on 3D Body Skeletons via Kernel Feature Maps—0
Motion-Depth: RGB-D Depth Map Enhancement with Motion and Depth in Complement—0
MotionDiff: Training-free Zero-shot Interactive Motion Editing via Flow-assisted Multi-view Diffusion—0
Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform—0
Motion Estimation for Large Displacements and Deformations—0
Motion Feature Network: Fixed Motion Filter for Action Recognition—0
CMRNext: Camera to LiDAR Matching in the Wild for Localization and Extrinsic Calibration—0
Video-based Bottleneck Detection utilizing Lagrangian Dynamics in Crowded Scenes—0
ClothFormer: Taming Video Virtual Try-On in All Module—0
Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimators—0
Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features—0
Motion-Guided Cascaded Refinement Network for Video Object Segmentation—0
Motion-Guided Global-Local Aggregation Transformer Network for Precipitation Nowcasting—0
Motion-inductive Self-supervised Object Discovery in Videos—0
Motion Prediction Under Multimodality with Conditional Stochastic Networks—0
Close-up View synthesis by Interpolating Optical Flow—0
CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation—0
Motion Representation with Acceleration Images—0
ClickBAIT: Click-based Accelerated Incremental Training of Convolutional Neural Networks—0
Motion Segmentation from a Moving Monocular Camera—0
MotionStone: Decoupled Motion Intensity Modulation with Diffusion Transformer for Image-to-Video Generation—0
Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation—0
Class agnostic moving target detection by color and location prediction of moving area—0
A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images—0
Movement Tracking by Optical Flow Assisted Inertial Navigation—0
MOVES: Manipulated Objects in Video Enable Segmentation—0
MoVideo: Motion-Aware Video Generation with Diffusion Models—0
Moving Indoor: Unsupervised Video Depth Learning in Challenging Environments—0
Moving Object Proposals with Deep Learned Optical Flow for Video Object Segmentation—0
Characterizing Human Behaviours Using Statistical Motion Descriptor—0
Characterizing and Improving Stability in Neural Style Transfer—0
MRF Optimization with Separable Convex Prior on Partially Ordered Labels—0
Mutual Suppression Network for Video Prediction using Disentangled Features—0
MS-nowcasting: Operational Precipitation Nowcasting with Convolutional LSTMs at Microsoft Weather—0
Abnormal Event Detection in Videos using Generative Adversarial Nets—0
Chaos in Motion: Unveiling Robustness in Remote Heart Rate Measurement through Brain-Inspired Skin Tracking—0
Multi-Action Recognition via Stochastic Modelling of Optical Flow and Gradients—0
Multidimensional Digital Filters for Point-Target Detection in Cluttered Infrared Scenes—0
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light—0
Abnormal Event Detection in Urban Surveillance Videos Using GAN and Transfer Learning—0
Non-contact PPG Signal and Heart Rate Estimation with Multi-hierarchical Convolutional Network—0
Channel-wise Motion Features for Efficient Motion Segmentation—0
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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