SOTAVerified

Motion Segmentation

Motion Segmentation is an essential task in many applications in Computer Vision and Robotics, such as surveillance, action recognition and scene understanding. The classic way to state the problem is the following: given a set of feature points that are tracked through a sequence of images, the goal is to cluster those trajectories according to the different motions they belong to. It is assumed that the scene contains multiple objects that are moving rigidly and independently in 3D-space.

Source: Robust Motion Segmentation from Pairwise Matches

Papers

Showing 111120 of 212 papers

TitleStatusHype
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding0
EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion SaliencyCode0
3D Rigid Motion Segmentation with Mixed and Unknown Number of Models0
Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model0
Motion Segmentation Using Locally Affine Atom Voting0
Progressive-X: Efficient, Anytime, Multi-Model Fitting AlgorithmCode1
UnOS: Unified Unsupervised Optical-Flow and Stereo-Depth Estimation by Watching VideosCode1
Robust Motion Segmentation from Pairwise MatchesCode0
Event-Based Motion Segmentation by Motion CompensationCode1
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rule BasedAccuracy90Unverified
2Rel-Att-GCNAccuracy89Unverified
3MRGCNAccuracy86Unverified
4MRGCN-LSTMAccuracy72Unverified
5St-RNNAccuracy63Unverified
#ModelMetricClaimedVerifiedStatus
1SSCClassification Error2.18Unverified
2T-LinkageClassification Error1.97Unverified
3RSIMClassification Error1.01Unverified
4MVCClassification Error0.31Unverified
#ModelMetricClaimedVerifiedStatus
1MultiViewClusteringError7.92Unverified
#ModelMetricClaimedVerifiedStatus
1MVCClassification Error0.65Unverified