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 51–100 of 2184 papers

TitleStatusHype
FlowDiffuser: Advancing Optical Flow Estimation with Diffusion ModelsCode2
Dense Optical Tracking: Connecting the DotsCode2
Flow-Guided Diffusion for Video InpaintingCode2
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-SupervisionCode2
Breaking of brightness consistency in optical flow with a lightweight CNN networkCode2
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editingCode2
Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback LearningCode2
Mask-Free Video Instance SegmentationCode2
Conditional Image-to-Video Generation with Latent Flow Diffusion ModelsCode2
Learning Optical Flow and Scene Flow with Bidirectional Camera-LiDAR FusionCode2
VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow EstimationCode2
InstMove: Instance Motion for Object-centric Video SegmentationCode2
Exploiting Optical Flow Guidance for Transformer-Based Video InpaintingCode2
CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical FlowCode2
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View CompletionCode2
User-Controllable Latent Transformer for StyleGAN Image Layout EditingCode2
Depth Field Networks for Generalizable Multi-view Scene RepresentationCode2
ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the WildCode2
PVO: Panoptic Visual OdometryCode2
IFRNet: Intermediate Feature Refine Network for Efficient Frame InterpolationCode2
Particle Video Revisited: Tracking Through Occlusions Using Point TrajectoriesCode2
FlowFormer: A Transformer Architecture for Optical FlowCode2
Deep Video Prior for Video Consistency and PropagationCode2
TransVOD: End-to-End Video Object Detection with Spatial-Temporal TransformersCode2
GMFlow: Learning Optical Flow via Global MatchingCode2
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo MatchingCode2
Learning to See Through ObstructionsCode2
Depth-Aware Video Frame InterpolationCode2
SDCNet: Video Prediction Using Spatially-Displaced ConvolutionCode2
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised TrainingCode1
MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style ConvolutionCode1
Princeton365: A Diverse Dataset with Accurate Camera PoseCode1
Spatio-Temporal State Space Model For Efficient Event-Based Optical FlowCode1
3DFlowAction: Learning Cross-Embodiment Manipulation from 3D Flow World ModelCode1
Zero-to-Hero: Zero-Shot Initialization Empowering Reference-Based Video Appearance EditingCode1
V2V: Scaling Event-Based Vision through Efficient Video-to-Voxel SimulationCode1
TT-DF: A Large-Scale Diffusion-Based Dataset and Benchmark for Human Body Forgery DetectionCode1
Asynchronous Multi-Object Tracking with an Event CameraCode1
MELLM: Exploring LLM-Powered Micro-Expression Understanding Enhanced by Subtle Motion PerceptionCode1
A Simple Detector with Frame Dynamics is a Strong TrackerCode1
VADMamba: Exploring State Space Models for Fast Video Anomaly DetectionCode1
Unsupervised Joint Learning of Optical Flow and Intensity with Event CamerasCode1
UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural NetworksCode1
Online Dense Point Tracking with Streaming MemoryCode1
EVLoc: Event-based Visual Localization in LiDAR Maps via Event-Depth RegistrationCode1
BF-STVSR: B-Splines and Fourier-Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection MethodCode1
BF-STVSR: B-Splines and Fourier---Best Friends for High Fidelity Spatial-Temporal Video Super-ResolutionCode1
Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for Self-Supervised Video DenoisingCode1
Learning Normal Flow Directly From Event NeighborhoodsCode1
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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
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