Optical Flow Estimation
652 papers with code • 10 benchmarks • 33 datasets
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
Benchmarks
These leaderboards are used to track progress in Optical Flow Estimation
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Libraries
Use these libraries to find Optical Flow Estimation models and implementationsDatasets
KITTI
FlyingThings3D
Vimeo90K
MPI Sintel
Virtual KITTI
MegaDepth
VisDrone
Event-Camera Dataset
N-CARS
MVSEC
Latest papers with no code
Deep-learning Optical Flow Outperforms PIV in Obtaining Velocity Fields from Active Nematics
Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks.
Structure-Aware Human Body Reshaping with Adaptive Affinity-Graph Network
Particularly, an SRM filter is utilized to extract high-frequency details, which are combined with spatial features as input to the BSD.
Attack on Scene Flow using Point Clouds
Robustness of these techniques, however, remains a concern, particularly in the face of adversarial attacks that have been proven to deceive state-of-the-art deep neural networks in many domains.
Turb-Seg-Res: A Segment-then-Restore Pipeline for Dynamic Videos with Atmospheric Turbulence
Tackling image degradation due to atmospheric turbulence, particularly in dynamic environment, remains a challenge for long-range imaging systems.
3D Multi-frame Fusion for Video Stabilization
In this paper, we present RStab, a novel framework for video stabilization that integrates 3D multi-frame fusion through volume rendering.
Vision-based control for landing an aerial vehicle on a marine vessel
This work addresses the landing problem of an aerial vehicle, exemplified by a simple quadrotor, on a moving platform using image-based visual servo control.
TempBEV: Improving Learned BEV Encoders with Combined Image and BEV Space Temporal Aggregation
These results indicate the overall effectiveness of our approach and make a strong case for aggregating temporal information in both image and BEV latent spaces.
Improving Bracket Image Restoration and Enhancement with Flow-guided Alignment and Enhanced Feature Aggregation
In this paper, we address the Bracket Image Restoration and Enhancement (BracketIRE) task using a novel framework, which requires restoring a high-quality high dynamic range (HDR) image from a sequence of noisy, blurred, and low dynamic range (LDR) multi-exposure RAW inputs.
FSRT: Facial Scene Representation Transformer for Face Reenactment from Factorized Appearance, Head-pose, and Facial Expression Features
The task of face reenactment is to transfer the head motion and facial expressions from a driving video to the appearance of a source image, which may be of a different person (cross-reenactment).
Table tennis ball spin estimation with an event camera
In table tennis, the combination of high velocity and spin renders traditional low frame rate cameras inadequate for quickly and accurately observing the ball's logo to estimate the spin due to the motion blur.
