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 601–650 of 2184 papers

TitleStatusHype
Can SAM Boost Video Super-Resolution?—0
Distracting Downpour: Adversarial Weather Attacks for Motion EstimationCode1
RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz PyramidCode0
Learning Dynamic Point Cloud Compression via Hierarchical Inter-frame Block MatchingCode0
FlowText: Synthesizing Realistic Scene Text Video with Optical Flow EstimationCode1
Weakly-supervised Micro- and Macro-expression Spotting Based on Multi-level Consistency—0
Event-Free Moving Object Segmentation from Moving Ego VehicleCode1
SSTM: Spatiotemporal Recurrent Transformers for Multi-frame Optical Flow EstimationCode0
Rip Current Detection in Nearshore Areas through UAV Video Analysis with Almost Local-Isometric Embedding Techniques on Sphere—0
TransFlow: Transformer as Flow Learner—0
FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving—0
Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual GroupingCode1
LLA-FLOW: A Lightweight Local Aggregation on Cost Volume for Optical Flow Estimation—0
Learning How To Robustly Estimate Camera Pose in Endoscopic VideosCode1
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B ImageryCode1
Neuromorphic Optical Flow and Real-time Implementation with Event Cameras—0
Fusing Structure from Motion and Simulation-Augmented Pose Regression from Optical Flow for Challenging Indoor Environments—0
Unsupervised Learning Optical Flow in Multi-frame Dynamic Environment Using Temporal Dynamic Modeling—0
Soundini: Sound-Guided Diffusion for Natural Video EditingCode1
MED-VT++: Unifying Multimodal Learning with a Multiscale Encoder-Decoder Video Transformer—0
Local-Global Temporal Difference Learning for Satellite Video Super-ResolutionCode1
Exposure Fusion for Hand-held Camera Inputs with Optical Flow and PatchMatch—0
Co-attention Propagation Network for Zero-Shot Video Object SegmentationCode0
MMVC: Learned Multi-Mode Video Compression with Block-based Prediction Mode Selection and Density-Adaptive Entropy CodingCode1
DEFLOW: Self-supervised 3D Motion Estimation of Debris FlowCode1
Decoupling Dynamic Monocular Videos for Dynamic View SynthesisCode1
A real-time algorithm for human action recognition in RGB and thermal video—0
Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots—0
Multi-view reconstruction of bullet time effect based on improved NSFF model—0
CapsFlow: Optical Flow Estimation with Capsule Networks—0
Decomposed Cross-modal Distillation for RGB-based Temporal Action Detection—0
AnyFlow: Arbitrary Scale Optical Flow with Implicit Neural Representation—0
Flow supervision for Deformable NeRF—0
TimeBalance: Temporally-Invariant and Temporally-Distinctive Video Representations for Semi-Supervised Action RecognitionCode1
Mask-Free Video Instance SegmentationCode2
VIVE3D: Viewpoint-Independent Video Editing using 3D-Aware GANsCode1
HQ3DAvatar: High Quality Controllable 3D Head Avatar—0
SUDS: Scalable Urban Dynamic Scenes—0
Unsupervised Hierarchical Domain Adaptation for Adverse Weather Optical Flow—0
Conditional Image-to-Video Generation with Latent Flow Diffusion ModelsCode2
DistractFlow: Improving Optical Flow Estimation via Realistic Distractions and Pseudo-Labeling—0
Learning Optical Flow and Scene Flow with Bidirectional Camera-LiDAR FusionCode2
TMA: Temporal Motion Aggregation for Event-based Optical FlowCode1
Learning Optical Flow from Event Camera with Rendered Dataset—0
Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationCode1
Video shutter angle estimation using optical flow and linear blur—0
Mutual Information-Based Temporal Difference Learning for Human Pose Estimation in Video—0
Rethinking Optical Flow from Geometric Matching Consistent PerspectiveCode1
VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow EstimationCode2
Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency LossesCode1
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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