most citedSemi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization

2 citations · 3 across the 2 of their papers we have counts for

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2 papers

cs.CV2023★ 2 cited

Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization

Wentao Pan, Zhe Xu, Jiangpeng Yan +4

Semi-supervised semantic segmentation aims to utilize limited labeled images and abundant unlabeled images to achieve label-efficient learning, wherein the weak-to-strong consisten…

eess.AS2023★ 1 cited

Speaker Embeddings as Individuality Proxy for Voice Stress Detection

Zihan Wu, Neil Scheidwasser-Clow, Karl El Hajal +1

Since the mental states of the speaker modulate speech, stress introduced by cognitive or physical loads could be detected in the voice. The existing voice stress detection benchma…