computer-vision-15
Compositional Zero-Shot Learning
3260 papers • 126 benchmarks • 313 datasets
Compositional Zero-Shot Learning (CZSL) is a computer vision task in which the goal is to recognize unseen compositions fromed from seen state and object during training. The key challenge in CZSL is the inherent entanglement between the state and object within the context of an image. Some example benchmarks for this task are MIT-states, UT-Zappos, and C-GQA. Models are usually evaluated with the Accuracy for both seen and unseen compositions, as well as their Harmonic Mean(HM). ( Image credit: Heosuab )
(Image credit: Papersgraph)
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MIT-States
MIT-States
MIT-States, generalized split
MIT-States, generalized split
UT-Zappos
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