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Unsupervised Object Segmentation On Fbms 59

Metrics

mIoU

Results

Performance results of various models on this benchmark

Paper Title
RCF (with post-processing)72.4Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping
RCF (without post-processing)69.9Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping
OCLR65.4Segmenting Moving Objects via an Object-Centric Layered Representation
MOD61.3Motion-inductive Self-supervised Object Discovery in Videos
GWM60.9Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion
TokenCut60.2TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
AMD47.5The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
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Unsupervised Object Segmentation On Fbms 59 | SOTA | HyperAI