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 1301–1350 of 2184 papers

TitleStatusHype
SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation—0
ATG-PVD: Ticketing Parking Violations on A Drone—0
RespVAD: Voice Activity Detection via Video-Extracted Respiration PatternsCode0
Exploring the Impacts from Datasets to Monocular Depth Estimation (MDE) Models with MineNavi—0
SegCodeNet: Color-Coded Segmentation Masks for Activity Detection from Wearable Cameras—0
Mesh Guided One-shot Face Reenactment using Graph Convolutional Networks—0
DTVNet: Dynamic Time-lapse Video Generation via Single Still ImageCode1
Learning to See Through Obstructions with Layered DecompositionCode1
Fast and Accurate Optical Flow based Depth Map Estimation from Light Fields—0
Real-Time Sign Language Detection using Human Pose Estimation—0
Self-Supervised Learning of Audio-Visual Objects from VideoCode1
2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework—0
A Flow-Guided Mutual Attention Network for Video-Based Person Re-Identification—0
Tracking in Crowd is Challenging: Analyzing Crowd based on Physical Characteristics—0
PAN: Towards Fast Action Recognition via Learning Persistence of AppearanceCode1
Optical Flow and Mode Selection for Learning-based Video Coding—0
A Novel Indoor Positioning System for unprepared firefighting scenarios—0
Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition—0
Memory-augmented Dense Predictive Coding for Video Representation LearningCode1
Hindsight for Foresight: Unsupervised Structured Dynamics Models from Physical Interaction—0
Unsupervised Learning of Optical Flow with Deep Feature Similarity—0
A Flexible Recurrent Residual Pyramid Network for Video Frame Interpolation—0
Is Sharing of Egocentric Video Giving Away Your Biometric Signature?—0
Entropy Minimisation Framework for Event-based Vision Model EstimationCode1
3D Fluid Flow Reconstruction Using Compact Light Field PIV—0
Polarized Optical-Flow Gyroscope—0
Self-supervised Motion Representation via Scattering Local Motion Cues—0
Unsupervised Learning of Particle Image VelocimetryCode1
Robust Ego and Object 6-DoF Motion Estimation and TrackingCode1
Change Detection Using Synthetic Aperture Radar Videos—0
MuCAN: Multi-Correspondence Aggregation Network for Video Super-ResolutionCode1
Learnable Cost Volume Using the Cayley RepresentationCode0
Beyond Single Stage Encoder-Decoder Networks: Deep Decoders for Semantic Image Segmentation—0
LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow EstimationCode1
Two-stream Fusion Model for Dynamic Hand Gesture Recognition using 3D-CNN and 2D-CNN Optical Flow guided Motion Template—0
SAILenv: Learning in Virtual Visual Environments Made SimpleCode0
CloudCast: A Satellite-Based Dataset and Baseline for Forecasting CloudsCode0
Leveraging Category Information for Single-Frame Visual Sound Source SeparationCode0
Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos—0
Distributed optimization for nonrigid nano-tomographyCode0
STaRFlow: A SpatioTemporal Recurrent Cell for Lightweight Multi-Frame Optical Flow EstimationCode1
Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer—0
Real-time Embedded Person Detection and Tracking for Shopping Behaviour Analysis—0
Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer—0
Learning Model-Blind Temporal Denoisers without Ground Truths—0
Low-light Environment Neural SurveillanceCode0
Learning Geocentric Object Pose in Oblique Monocular ImagesCode1
FlowControl: Optical Flow Based Visual Servoing—0
A Framework for Learning Invariant Physical Relations in Multimodal Sensory Processing—0
OccInpFlow: Occlusion-Inpainting Optical Flow Estimation by Unsupervised Learning—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