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
Triple-stream Deep Metric Learning of Great Ape Behavioural Actions—0
STEPs: Self-Supervised Key Step Extraction and Localization from Unlabeled Procedural VideosCode0
Time-to-Contact Map by Joint Estimation of Up-to-Scale Inverse Depth and Global Motion using a Single Event Camera—0
Unsupervised Space-Time Network for Temporally-Consistent Segmentation of Multiple MotionsCode0
Frame Interpolation Transformer and Uncertainty Guidance—0
Learning Optical Expansion From Scale MatchingCode0
SelfME: Self-Supervised Motion Learning for Micro-Expression Recognition—0
MOVES: Manipulated Objects in Video Enable Segmentation—0
StepNet: Spatial-temporal Part-aware Network for Isolated Sign Language Recognition—0
Fast Event-based Optical Flow Estimation by Triplet Matching—0
Open-Vocabulary Temporal Action Detection with Off-the-Shelf Image-Text Features—0
CGCV:Context Guided Correlation Volume for Optical Flow Neural Networks—0
ColoristaNet for Photorealistic Video Style Transfer—0
Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration—0
Motion and Context-Aware Audio-Visual Conditioned Video Prediction—0
DroneAttention: Sparse Weighted Temporal Attention for Drone-Camera Based Activity Recognition—0
Neural Cell Video Synthesis via Optical-Flow Diffusion—0
Self-supervised AutoFlow—0
Face Animation with Multiple Source Images—0
HashEncoding: Autoencoding with Multiscale Coordinate Hashing—0
Motion-Guided Global-Local Aggregation Transformer Network for Precipitation Nowcasting—0
Vision-based localization methods under GPS-denied conditions—0
Boosting Object Representation Learning via Motion and Object ContinuityCode0
SATVSR: Scenario Adaptive Transformer for Cross Scenarios Video Super-Resolution—0
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping—0
FlowGrad: Using Motion for Visual Sound Source LocalizationCode0
Progressive Motion Context Refine Network for Efficient Video Frame Interpolation—0
SWTF: Sparse Weighted Temporal Fusion for Drone-Based Activity Recognition—0
Prior-enhanced Temporal Action Localization using Subject-aware Spatial Attention—0
Efficient Unsupervised Video Object Segmentation Network Based on Motion Guidance—0
Two-stream Multi-dimensional Convolutional Network for Real-time Violence Detection—0
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks—0
Detection of (Hidden) Emotions from Videos using Muscles Movements and Face Manifold Embedding—0
Real-time AdaBoost cascade face tracker based on likelihood map and optical flow—0
CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation—0
Attacking Motion Estimation with Adversarial Snow—0
Spatio-Temporal-based Context Fusion for Video Anomaly Detection—0
A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution—0
LAD: A Hybrid Deep Learning System for Benign Paroxysmal Positional Vertigo Disorders Diagnostic—0
Real-time Action Recognition for Fine-Grained Actions and The Hand Wash DatasetCode0
PSNet: Parallel Symmetric Network for Video Salient Object Detection—0
Weakly-Supervised Optical Flow Estimation for Time-of-FlightCode0
DeepHS-HDRVideo: Deep High Speed High Dynamic Range Video Reconstruction—0
Facial Expression Spotting Based on Optical Flow FeaturesCode0
Students taught by multimodal teachers are superior action recognizers—0
Visual Looming from Motion Field and Surface Normals—0
Self-Aligned Concave Curve: Illumination Enhancement for Unsupervised Adaptation—0
WorldGen: A Large Scale Generative Simulator—0
Motion-inductive Self-supervised Object Discovery in Videos—0
Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications—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
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