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 110 of 212 papers

TitleStatusHype
Channel-wise Motion Features for Efficient Motion Segmentation0
Temporal Rate Reduction Clustering for Human Motion Segmentation0
KDMOS:Knowledge Distillation for Motion SegmentationCode0
FreeGave: 3D Physics Learning from Dynamic Videos by Gaussian VelocityCode1
EV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras0
Event-based Egocentric Human Pose Estimation in Dynamic Environment0
Iterative Event-based Motion Segmentation by Variational Contrast MaximizationCode0
Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction0
BEVMOSNet: Multimodal Fusion for BEV Moving Object Segmentation0
Wandering around: A bioinspired approach to visual attention through object motion sensitivityCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SSCClassification Error2.18Unverified
2T-LinkageClassification Error1.97Unverified
3RSIMClassification Error1.01Unverified
4MVCClassification Error0.31Unverified