Classification Consistency
5 papers with code • 0 benchmarks • 0 datasets
How often two shifts of the same image are classified the same
( Image credit: Antialiased CNNs )
Benchmarks
These leaderboards are used to track progress in Classification Consistency
Most implemented papers
Making Convolutional Networks Shift-Invariant Again
The well-known signal processing fix is anti-aliasing by low-pass filtering before downsampling.
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity
optimization-ai/icml2023_ldr
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We study a family of loss functions named label-distributionally robust (LDR) losses for multi-class classification that are formulated from distributionally robust optimization (DRO) perspective, where the uncertainty in the given label information are modeled and captured by taking the worse case of distributional weights.
End-to-End Semi-Supervised Learning for Video Action Detection
AKASH2907/End-to-End-Semi-Supervised-Learning-for-Video-Action-Detection
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CVPR 2022
In this work, we focus on semi-supervised learning for video action detection which utilizes both labeled as well as unlabeled data.
Implicit Generative Prior for Bayesian Neural Networks
yjliu7/neural-adaptive-empirical-bayes
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The results of our experiments highlight the superiority of our proposed framework over existing methods, such as sparse variational Bayesian and generative models, in terms of prediction accuracy and uncertainty quantification.
Dual-stage Hyperspectral Image Classification Model with Spectral Supertoken
laprf/dstc
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Hyperspectral image classification, a task that assigns pre-defined classes to each pixel in a hyperspectral image of remote sensing scenes, often faces challenges due to the neglect of correlations between spectrally similar pixels.
