HyperAI

Semi Supervised Video Object Segmentation On 1

Metrics

F-measure (Mean)
FPS
Ju0026F
Jaccard (Mean)

Results

Performance results of various models on this benchmark

Comparison Table
Model NameF-measure (Mean)FPSJu0026FJaccard (Mean)
associating-objects-with-scalable86.612.082.778.8
xmem-long-term-video-object-segmentation-with84.7-81.277.6
associating-objects-with-transformers-for85.112.181.277.3
premvos-proposal-generation-refinement-and75.8-71.667.5
associating-objects-with-scalable87.91.384.581.0
video-object-segmentation-without-temporal62.1-57.552.9
learning-quality-aware-dynamic-memory-for85.4-81.978.1
lsmvos-long-short-term-similarity-matching71.2-67.463.7
xmem-long-term-video-object-segmentation-with87.0-83.780.5
collaborative-video-object-segmentation-by-181.6-78.074.4
tracking-anything-with-decoupled-video86.825.383.279.6
decoupling-features-in-hierarchical79.049.275.471.9
modular-interactive-video-object-segmentation80.2-76.572.7
capsulevos-semi-supervised-video-object55.2-51.347.4
collaborative-video-object-segmentation-by78.5-74.871.1
efficient-regional-memory-network-for-video78.1-75.071.9
efficient-video-object-segmentation-via--41.337.7
associating-objects-with-transformers-for82.318.778.374.3
reliable-propagation-correction-modulation82.6-79.275.8
xmem-long-term-video-object-segmentation-with85.8-82.579.1
kernelized-memory-network-for-video-object80.3-77.274.1
reliable-propagation-correction-modulation84.3-8177.6
memory-matching-is-not-enough-jointly87.4-83.980.3
fast-video-object-segmentation-by-reference54.4-52.851.3
lucid-data-dreaming-for-video-object69.9-66.663.4
decoupling-features-in-hierarchical79.940.976.272.5
ranet-ranking-attention-network-for-fast57.3-55.453.4
associating-objects-with-scalable81.724.378.174.5
hierarchical-memory-matching-network-for82.5-78.674.7
associating-objects-with-transformers-for75.751.472.068.3
associating-objects-with-scalable83.617.579.976.2
one-shot-video-object-segmentation--50.947.0
xmem-long-term-video-object-segmentation-with86.4-83.179.7
decoupling-features-in-hierarchical81.728.577.974.1
associating-objects-with-transformers-for77.540.073.970.3
associating-objects-with-transformers-for79.329.675.571.6
fast-online-object-tracking-and-segmentation45.8-43.240.6
online-adaptation-of-convolutional-neural--52.849.9
decoupling-features-in-hierarchical77.363.573.770.0
decoupling-features-in-hierarchical84.527.080.776.9
fast-and-accurate-online-video-object44.2-43.642.9
video-object-segmentation-using-space-time75.2-72.269.3
feelvos-fast-end-to-end-embedding-learning60.4-57.855.1
decoupling-features-in-hierarchical86.715.482.878.9
19040814172.7-69.566.4
putting-the-object-back-into-video-object89.936.486.182.4
putting-the-object-back-into-video-object89.217.985.982.6
siam-r-cnn-visual-tracking-by-re-detection58.6-53.348.0
rethinking-space-time-networks-with-improved83.5-79.976.3
rvos-end-to-end-recurrent-network-for-video52.6-50.347.9
xmem-long-term-video-object-segmentation-with84.5-81.077.4
associating-objects-with-transformers-for83.318.079.675.9
cnn-in-mrf-video-object-segmentation-via70.5-67.564.5
a-generative-appearance-model-for-end-to-end55.3-52.349.2
associating-objects-with-scalable88.51.384.780.9
make-one-shot-video-object-segmentation-168.6-64.860.9
separable-structure-modeling-for-semi63.8-62.060.2
putting-the-object-back-into-video-object91.417.988.184.7
xmem-long-term-video-object-segmentation-with83.4-79.876.3