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 851–900 of 2184 papers

TitleStatusHype
Demonstration of Vector Flow Imaging using Convolutional Neural Networks—0
Beyond Brightness Constancy: Learning Noise Models for Optical Flow—0
Analytic Signal Phase in N-D by Linear Symmetry Tensor--fingerprint modeling—0
Adaptive Semantic-Spatio-Temporal Graph Convolutional Network for Lip Reading—0
3D wind field profiles from hyperspectral sounders: revisiting optic-flow from a meteorological perspective—0
DemMamba: Alignment-free Raw Video Demoireing with Frequency-assisted Spatio-Temporal Mamba—0
BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving—0
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms—0
DeGraF-Flow: Extending DeGraF Features for accurate and efficient sparse-to-dense optical flow estimation—0
Deformation Monitoring of Tunnel using Phase-based Motion Magnification and Optical Flow—0
Best Vision Technologies Submission to ActivityNet Challenge 2018-Task: Dense-Captioning Events in Videos—0
Improve Myocardial Strain Estimation based on Deformable Groupwise Registration with a Locally Low-Rank Dissimilarity Metric—0
Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation—0
Analysis of Latent-Space Motion for Collaborative Intelligence—0
DeepVIO: Self-supervised Deep Learning of Monocular Visual Inertial Odometry using 3D Geometric Constraints—0
A Multi-stream Convolutional Neural Network for Micro-expression Recognition Using Optical Flow and EVM—0
Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: a Review—0
Handcrafted localized phase features for human action recognition—0
Handcrafted Local Features are Convolutional Neural Networks—0
Self-supervising Action Recognition by Statistical Moment and Subspace Descriptors—0
A Multi-Stream Bi-Directional Recurrent Neural Network for Fine-Grained Action Detection—0
Adaptive mixed norm optical flow estimation—0
3D Velocity from 3D Doppler Radial Velocity—0
2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework—0
Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs—0
GyroFlow+: Gyroscope-Guided Unsupervised Deep Homography and Optical Flow Learning—0
Deep Video Codec Control for Vision Models—0
Guided Optical Flow Learning—0
Deep Two-Stream Video Inference for Human Body Pose and Shape Estimation—0
BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation—0
A Multi-Modal Transformer Network for Action Detection—0
Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction—0
Group Activity Recognition using Unreliable Tracked Pose—0
Deep Transport Network for Unsupervised Video Object Segmentation—0
Group Activity Recognition by Using Effective Multiple Modality Relation Representation With Temporal-Spatial Attention—0
Deep Transfer Learning for EEG-based Brain Computer Interface—0
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion—0
Guidance system for Visually Impaired Persons using Deep Learning and Optical flow—0
Graph Neural Network Combining Event Stream and Periodic Aggregation for Low-Latency Event-based Vision—0
Deep-Temporal LSTM for Daily Living Action Recognition—0
GPU Accelerated Color Correction and Frame Warping for Real-time Video Stitching—0
HairFIT: Pose-Invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-Region-Aware Inpainting—0
Deep Temporal Interpolation of Radar-based Precipitation—0
Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous Vehicles—0
Batch-Based Activity Recognition from Egocentric Photo-Streams—0
Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation—0
Adaptive Intermediate Representations for Video Understanding—0
Google Map Aided Visual Navigation for UAVs in GPS-denied Environment—0
Deep soccer captioning with transformer: dataset, semantics-related losses, and multi-level evaluation—0
Balancing Domain Experts for Long-Tailed Camera-Trap Recognition—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