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 1101–1150 of 2184 papers

TitleStatusHype
Optical Flow Regularization of Implicit Neural Representations for Video Frame Interpolation—0
Colonoscopy 3D Video Dataset with Paired Depth from 2D-3D Registration—0
HairFIT: Pose-Invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-Region-Aware Inpainting—0
GateHUB: Gated History Unit with Background Suppression for Online Action Detection—0
Audio-video fusion strategies for active speaker detection in meetings—0
Unsupervised Learning of 3D Scene Flow from Monocular CameraCode0
TadML: A fast temporal action detection with Mechanics-MLPCode0
3D Convolutional with Attention for Action Recognition—0
Physically Inspired Constraint for Unsupervised Regularized Ultrasound Elastography—0
Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2021—0
Sign Language Video Anonymization—0
MSTCGAN: Multiscale time conditional generative adversarial network for long-term satellite image sequence predictionCode0
Feature-Aligned Video Raindrop Removal with Temporal Constraints—0
DeepRM: Deep Recurrent Matching for 6D Pose Refinement—0
FlowNet-PET: Unsupervised Learning to Perform Respiratory Motion Correction in PET ImagingCode0
Unsupervised Learning of Depth, Camera Pose and Optical Flow from Monocular Video—0
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion—0
A Framework for Event-based Computer Vision on a Mobile DeviceCode0
Dynamic Dense RGB-D SLAM using Learning-based Visual Odometry—0
Data-Driven Optimal Sensor Placement for High-Dimensional System Using Annealing Machine—0
EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms—0
Exploiting Correspondences with All-pairs Correlations for Multi-view Depth Estimation—0
Handcrafted localized phase features for human action recognition—0
RAFT-MSF: Self-Supervised Monocular Scene Flow using Recurrent Optimizer—0
GeoRefine: Self-Supervised Online Depth Refinement for Accurate Dense Mapping—0
Object Class Aware Video Anomaly Detection through Image Translation—0
Emotion-Controllable Generalized Talking Face Generation—0
Video Frame Interpolation Based on Deformable Kernel RegionCode0
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition—0
A qualitative investigation of optical flow algorithms for video denoising—0
Lagrangian Motion Magnification with Double Sparse Optical Flow DecompositionCode0
Autonomous Satellite Detection and Tracking using Optical Flow—0
Imposing Consistency for Optical Flow Estimation—0
Event TransformerCode0
HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area SurveillanceCode0
Optical flow GNSS for navigation in the Indian subcontinent (NavIC)—0
A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency—0
Sparse Optical Flow-Based Line Feature Tracking—0
Unsupervised Coherent Video Cartoonization with Perceptual Motion ConsistencyCode0
Weakly Supervised Regional and Temporal Learning for Facial Action Unit Recognition—0
Revisiting Document Image Dewarping by Grid Regularization—0
A Temporal Learning Approach to Inpainting Endoscopic Specularities and Its effect on Image Correspondence—0
Are High-Resolution Event Cameras Really Needed?—0
Learning Optical Flow, Depth, and Scene Flow without Real-World Labels—0
DNN-Driven Compressive Offloading for Edge-Assisted Semantic Video Segmentation—0
On the Viability of Monocular Depth Pre-training for Semantic SegmentationCode0
Microstructure Surface Reconstruction from SEM Images: An Alternative to Digital Image Correlation (DIC)—0
DiffPoseNet: Direct Differentiable Camera Pose Estimation—0
Disentangling Architecture and Training for Optical Flow—0
Optical Flow for Video Super-Resolution: A Survey—0
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All datasetsSintel-cleanSintel-finalKITTI 2015 (train)KITTI 2015KITTI 2012SpringSintel Clean unsupervisedSintel Final unsupervisedKITTI 2015 unsupervisedKITTI 2012 unsupervised

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
4LiteFlowNet-ftAverage End-Point Error5.38—Unverified
5MR-FlowAverage 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
2IRR-PWCAverage End-Point Error1.6—Unverified
3LiteFlowNet-ftAverage End-Point Error1.6—Unverified
4PWC-Net + ft - axXivAverage End-Point Error1.5—Unverified
5FDFlowNet-ftAverage End-Point Error1.5—Unverified
6SelFlowAverage End-Point Error1.5—Unverified
7LiteFlowNet2-ftAverage End-Point Error1.4—Unverified
8LiteFlowNet3Average End-Point Error1.3—Unverified
9LiteFlowNet3-SAverage End-Point Error1.3—Unverified
10MaskFlownet-SAverage 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