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 1001–1050 of 2184 papers

TitleStatusHype
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos—0
Connect the Dots: In Situ 4D Seismic Monitoring of CO2 Storage with Spatio-temporal CNNs—0
EventDiff: A Unified and Efficient Diffusion Model Framework for Event-based Video Frame Interpolation—0
Toward Better Understanding of Saliency Prediction in Augmented 360 Degree Videos—0
Learning semantical dynamics and spatiotemporal collaboration for human pose estimation in video—0
Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition—0
Confused Modulo Projection based Somewhat Homomorphic Encryption -- Cryptosystem, Library and Applications on Secure Smart Cities—0
Joint Optical Flow and Temporally Consistent Semantic Segmentation—0
Joint Self-supervised Depth and Optical Flow Estimation towards Dynamic Objects—0
Joint Semantic and Motion Segmentation for dynamic scenes using Deep Convolutional Networks—0
Event-based vision on FPGAs -- a survey—0
Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization—0
JOLO-GCN: Mining Joint-Centered Light-Weight Information for Skeleton-Based Action Recognition—0
Just Dance with π! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection—0
A Robust Lane Detection and Departure Warning System—0
Event-based vision for egomotion estimation using precise event timing—0
DiffPoseNet: Direct Differentiable Camera Pose Estimation—0
Key frames assisted hybrid encoding for photorealistic compressive video sensing—0
Event-based Video Frame Interpolation with Edge Guided Motion Refinement—0
Conformalized Multimodal Uncertainty Regression and Reasoning—0
"Knights": First Place Submission for VIPriors21 Action Recognition Challenge at ICCV 2021—0
DIFT: Dynamic Iterative Field Transforms for Memory Efficient Optical Flow—0
Confidence-guided Adaptive Gate and Dual Differential Enhancement for Video Salient Object Detection—0
A robust and efficient video representation for action recognition—0
Event-based Moving Object Detection and Tracking—0
Conditional Video Generation Using Action-Appearance Captions—0
A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View—0
Learning Representative Temporal Features for Action Recognition—0
EvConv: Fast CNN Inference on Event Camera Inputs For High-Speed Robot Perception—0
Evaluation of the Spatio-Temporal features and GAN for Micro-expression Recognition System—0
A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline—0
eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks—0
Estimation of Linear Motion in Dense Crowd Videos using Langevin Model—0
A Flexible Recurrent Residual Pyramid Network for Video Frame Interpolation—0
Estimation of Clinical Workload and Patient Activity using Deep Learning and Optical Flow—0
Computational Motility Tracking of Calcium Dynamics in Toxoplasma gondii—0
Estimating motion with principal component regression strategies—0
Are High-Resolution Event Cameras Really Needed?—0
Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms—0
Learning Rank Reduced Interpolation with Principal Component Analysis—0
Learning Residual Flow as Dynamic Motion from Stereo Videos—0
Learning Spatiotemporal Features for Infrared Action Recognition with 3D Convolutional Neural Networks—0
Learning to Extract Motion from Videos in Convolutional Neural Networks—0
Leveraging Structural Context Models and Ranking Score Fusion for Human Interaction Prediction—0
Estimating Dynamic Flow Features in Groups of Tracked Objects—0
ES-MVSNet: Efficient Framework for End-to-end Self-supervised Multi-View Stereo—0
A Fine-Grained Visual Attention Approach for Fingerspelling Recognition in the Wild—0
Error-Aware Spatial Ensembles for Video Frame Interpolation—0
EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow—0
Compressive Coded Aperture Keyed Exposure Imaging with Optical Flow Reconstruction—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