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 801–850 of 2184 papers

TitleStatusHype
FlowTrack: Revisiting Optical Flow for Long-Range Dense Tracking—0
FlowVid: Taming Imperfect Optical Flows for Consistent Video-to-Video Synthesis—0
FlowVOS: Weakly-Supervised Visual Warping for Detail-Preserving and Temporally Consistent Single-Shot Video Object Segmentation—0
FlowWeb: Joint Image Set Alignment by Weaving Consistent, Pixel-Wise Correspondences—0
FluentLip: A Phonemes-Based Two-stage Approach for Audio-Driven Lip Synthesis with Optical Flow Consistency—0
Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation—0
Asymmetric Bilateral Phase Correlation for Optical Flow Estimation in the Frequency Domain—0
Exposure Fusion for Hand-held Camera Inputs with Optical Flow and PatchMatch—0
Exploring Weak Stabilization for Motion Feature Extraction—0
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping—0
"Forget" the Forget Gate: Estimating Anomalies in Videos using Self-contained Long Short-Term Memory Networks—0
Weakly Supervised LiDAR Semantic Segmentation via Scatter Image Annotation—0
FPCR-Net: Feature Pyramidal Correlation and Residual Reconstruction for Optical Flow Estimation—0
FPPN: Future Pseudo-LiDAR Frame Prediction for Autonomous Driving—0
Counting people from above: Airborne video based crowd analysis—0
hARMS: A Hardware Acceleration Architecture for Real-Time Event-Based Optical Flow—0
Frame-Recurrent Video Inpainting by Robust Optical Flow Inference—0
Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation—0
FreeDriveRF: Monocular RGB Dynamic NeRF without Poses for Autonomous Driving via Point-Level Dynamic-Static Decoupling—0
FreeGaussian: Guidance-free Controllable 3D Gaussian Splats with Flow Derivatives—0
Freespace Optical Flow Modeling for Automated Driving—0
Free Supervision From Video Games—0
Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow—0
A Survey on Backbones for Deep Video Action Recognition—0
Deep learning based fence segmentation and removal from an image using a video sequence—0
Exploring Self-Attention for Visual Odometry—0
FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving—0
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance, Head-pose, and Facial Expression Features—0
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance Head-pose and Facial Expression Features—0
FTFDNet: Learning to Detect Talking Face Video Manipulation with Tri-Modality Interaction—0
Aggregation of local parametric candidates with exemplar-based occlusion handling for optical flow—0
HashEncoding: Autoencoding with Multiscale Coordinate Hashing—0
Fully Automated Hand Hygiene Monitoring\ Operating Room using 3D Convolutional Neural Network—0
FUN-SIS: a Fully UNsupervised approach for Surgical Instrument Segmentation—0
FuseMODNet: Real-Time Camera and LiDAR based Moving Object Detection for robust low-light Autonomous Driving—0
Fusing Frame and Event Vision for High-speed Optical Flow for Edge Application—0
Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos—0
Fusing Structure from Motion and Simulation-Augmented Pose Regression from Optical Flow for Challenging Indoor Environments—0
Exploring Optical Flow Inclusion into nnU-Net Framework for Surgical Instrument Segmentation—0
Exploring Optical-Flow-Guided Motion and Detection-Based Appearance for Temporal Sentence Grounding—0
Exploring Motion Ambiguity and Alignment for High-Quality Video Frame Interpolation—0
Exploring More from Multiple Gait Modalities for Human Identification—0
CoT-AMFlow: Adaptive Modulation Network with Co-Teaching Strategy for Unsupervised Optical Flow Estimation—0
A Survey of Representation Learning, Optimization Strategies, and Applications for Omnidirectional Vision—0
Exploring Human Crowd Patterns and Categorization in Video Footage for Enhanced Security and Surveillance using Computer Vision and Machine Learning—0
Future frame prediction in chest cine MR imaging using the PCA respiratory motion model and dynamically trained recurrent neural networks—0
KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance—0
GateHUB: Gated History Unit with Background Suppression for Online Action Detection—0
GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation—0
CoSEC: A Coaxial Stereo Event Camera Dataset for Autonomous Driving—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