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 161170 of 212 papers

TitleStatusHype
Parametric Object Motion from Blur0
ProgressiveMotionSeg: Mutually Reinforced Framework for Event-Based Motion Segmentation0
Quantum Motion Segmentation0
Quickest Moving Object Detection0
Reconstructing Articulated Rigged Models from RGB-D Videos0
ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering0
Retina-Inspired Object Motion Segmentation for Event-Cameras0
Rigid Motion Segmentation using Randomized Voting0
Robust Multi-body Feature Tracker: A Segmentation-free Approach0
Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model0
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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