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 651–700 of 2184 papers

TitleStatusHype
Deep Curiosity Loops in Social Environments—0
Deep Crisp Boundaries: From Boundaries to Higher-level Tasks—0
Deep Crisp Boundaries—0
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition—0
DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry—0
AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras—0
Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition—0
Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow—0
A Universal Railway Obstacle Detection System based on Semi-supervised Segmentation And Optical Flow—0
Deep 360^ Optical Flow Estimation Based on Multi-Projection Fusion—0
A Unified Solution to Video Fusion: From Multi-Frame Learning to Benchmarking—0
Decomposed Cross-modal Distillation for RGB-based Temporal Action Detection—0
A Convolutional Feature Map based Deep Network targeted towards Traffic Detection and Classification—0
FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow—0
3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion—0
DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM—0
A Unified Method for First and Third Person Action Recognition—0
AI pipeline for accurate retinal layer segmentation using OCT 3D images—0
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation—0
FlowFusion: Dynamic Dense RGB-D SLAM Based on Optical Flow—0
Flow Guided Recurrent Neural Encoder for Video Salient Object Detection—0
DDCNet-Multires: Effective Receptive Field Guided Multiresolution CNN for Dense Prediction—0
DDCNet: Deep Dilated Convolutional Neural Network for Dense Prediction—0
Audio-Visual Target Speaker Enhancement on Multi-Talker Environment using Event-Driven Cameras—0
DCVNet: Dilated Cost Volume Networks for Fast Optical Flow—0
DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation—0
Audio-visual speech separation based on joint feature representation with cross-modal attention—0
DATAP-SfM: Dynamic-Aware Tracking Any Point for Robust Structure from Motion in the Wild—0
Audio-video fusion strategies for active speaker detection in meetings—0
Data-Driven Optimal Sensor Placement for High-Dimensional System Using Annealing Machine—0
3DPeople: Modeling the Geometry of Dressed Humans—0
Flow Distillation Sampling: Regularizing 3D Gaussians with Pre-trained Matching Priors—0
DASC: Dense Adaptive Self-Correlation Descriptor for Multi-Modal and Multi-Spectral Correspondence—0
Exploring Attention Mechanisms in Integration of Multi-Modal Information for Sign Language Recognition and Translation—0
Dance Any Beat: Blending Beats with Visuals in Dance Video Generation—0
DAISY Filter Flow: A Generalized Discrete Approach to Dense Correspondences—0
FlowDA: Unsupervised Domain Adaptive Framework for Optical Flow Estimation—0
A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation—0
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information—0
FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition—0
A Hybrid CNN-LSTM model for Video Deepfake Detection by Leveraging Optical Flow Features—0
CTRL-GS: Cascaded Temporal Residue Learning for 4D Gaussian Splatting—0
FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow—0
FlowControl: Optical Flow Based Visual Servoing—0
FlowDepth: Decoupling Optical Flow for Self-Supervised Monocular Depth Estimation—0
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition—0
Crowd Flow Segmentation in Compressed Domain using CRF—0
Attacking Motion Estimation with Adversarial Snow—0
Cross Pixel Optical Flow Similarity for Self-Supervised Learning—0
Cross-Modal Message Passing for Two-stream Fusion—0
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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
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