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 1751–1800 of 2184 papers

TitleStatusHype
Semantic Flow-guided Motion Removal Method for Robust Mapping—0
Texture-Based Input Feature Selection for Action Recognition—0
Semantic Video Segmentation by Gated Recurrent Flow Propagation—0
An initial attempt of combining visual selective attention with deep reinforcement learning—0
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks—0
Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation—0
AnimalMotionCLIP: Embedding motion in CLIP for Animal Behavior Analysis—0
Video Salient Object Detection via Contrastive Features and Attention Modules—0
A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging—0
A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding—0
Video Salient Object Detection via Fully Convolutional Networks—0
A Network for structural dense displacement based on 3D deformable mesh model and optical flow—0
An End-to-End Two-Stream Network Based on RGB Flow and Representation Flow for Human Action Recognition—0
SfM-Net: Learning of Structure and Motion from Video—0
An End-to-End Edge Aggregation Network for Moving Object Segmentation—0
Shape and Texture: What Influences Reliable Optical Flow Estimation?—0
An Empirical Study of Visual Features for DNN based Audio-Visual Speech Enhancement in Multi-talker Environments—0
SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning—0
Short-term prediction of localized cloud motion using ground-based sky imagers—0
Video Segmentation via Object Flow—0
3D Fluid Flow Reconstruction Using Compact Light Field PIV—0
Signal Alignment for Humanoid Skeletons via the Globally Optimal Reparameterization Algorithm—0
YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark—0
Sign Language Video Anonymization—0
SignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning—0
Sim2real transfer learning for 3D human pose estimation: motion to the rescue—0
Simulation of optical flow and fuzzy based obstacle avoidance system for mobile robots—0
SimulFlow: Simultaneously Extracting Feature and Identifying Target for Unsupervised Video Object Segmentation—0
Simultaneous 3D Reconstruction for Water Surface and Underwater Scene—0
Video shutter angle estimation using optical flow and linear blur—0
Simultaneous Optical Flow and Intensity Estimation From an Event Camera—0
Simultaneous Optical Flow and Segmentation (SOFAS) using Dynamic Vision Sensor—0
Single-frame Regularization for Temporally Stable CNNs—0
Single Image Action Recognition by Predicting Space-Time Saliency—0
Single Image Optical Flow Estimation with an Event Camera—0
Sistema de Navegação Autônomo Baseado em Visão Computacional—0
Skeleton-based Relational Reasoning for Group Activity Analysis—0
An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes—0
Skills Made to Order: Efficient Acquisition of Robot Cooking Skills Guided by Multiple Forms of Internet Data—0
Skin the sheep not only once: Reusing Various Depth Datasets to Drive the Learning of Optical Flow—0
SlowFast Rolling-Unrolling LSTMs for Action Anticipation in Egocentric Videos—0
Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data—0
Small Obstacle Avoidance Based on RGB-D Semantic Segmentation—0
Smart City Transportation: Deep Learning Ensemble Approach for Traffic Accident Detection—0
An optical flow approach to tracking ship track behavior using GOES-R satellite imagery—0
An Efficient Approach for Muscle Segmentation and 3D Reconstruction Using Keypoint Tracking in MRI Scan—0
Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration—0
Solving Dense Image Matching in Real-Time using Discrete-Continuous Optimization—0
Solving Low-Dose CT Reconstruction via GAN with Local Coherence—0
Some Aspects of Geometric Computer Vision for Analysing Dynamical Scenes focusing Automotive Applications—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