computer-vision-9

Semi-Supervised Video Classification

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

M. Shah, Y. Rawat, Mamshad Nayeem Rizve, Kevin Duarte•Thu Jan 14 2021

This work proposes an uncertainty-aware pseudo-label selection (UPS) framework which improves pseudo labeling accuracy by drastically reducing the amount of noise encountered in the training process and generalizes the pseudo- labeling process, allowing for the creation of negative pseudo-labels.

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Iterative weak/self-supervised classification framework for abnormal events detection

Hugo Proença, Bruno Degardin•Thu Dec 31 2020

This paper introduces one iterative learning framework composed of two experts working in the weak and self-supervised paradigms and providing additional amounts of learning data to each other, where the novel instances at each iteration are edited by a Bayesian framework that supports the iterative data augmentation task.

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Iterative Contrast-Classify For Semi-supervised Temporal Action Segmentation

Angela Yao, Dipika Singhania, R. Rahaman•Wed Dec 01 2021

This work proposes a novel way to learn frame-wise representations from temporal convolutional networks (TCNs) by clustering input features with added time-proximity conditions and multi-resolution similarity by merging representation learning with conventional supervised learning.

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