Historical Color Image Dating

4 papers with code • 1 benchmarks • 1 datasets

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Most implemented papers

Non-parametric Uni-modality Constraints for Deep Ordinal Classification

sbelharbi/Deep-Ordinal-Classification-with-Inequality-Constraints 25 Nov 2019

We propose a new constrained-optimization formulation for deep ordinal classification, in which uni-modality of the label distribution is enforced implicitly via a set of inequality constraints over all the pairs of adjacent labels.

Deep Ordinal Regression with Label Diversity

axeber01/dold 29 Jun 2020

By discretizing the target into a set of non-overlapping classes, it has been shown that training a classifier can improve neural network accuracy compared to using a standard regression approach.

Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression

Li-Wanhua/POEs CVPR 2021

An ordinal distribution constraint is proposed to exploit the ordinal nature of regression.

OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression

xk-huang/OrdinalCLIP 6 Jun 2022

In this paper, we propose to learn the rank concepts from the rich semantic CLIP latent space.