TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Human action generation	Human3.6M	c-GAN	MMDa	0.161	# 3
Human action generation	Human3.6M	c-GAN	MMDs	0.187	# 3
Human action generation	NTU RGB+D	c-GAN	FID (CS)	27.480	# 3
Human action generation	NTU RGB+D	c-GAN	FID (CV)	31.875	# 3
Human action generation	NTU RGB+D 120	c-GAN	FID (CS)	54.403	# 2
Human action generation	NTU RGB+D 120	c-GAN	FID (CV)	58.531	# 2
Human action generation	NTU RGB+D 2D	c-GAN	MMDa (CS)	0.334	# 3
Human action generation	NTU RGB+D 2D	c-GAN	MMDs (CS)	0.354	# 3
Human action generation	NTU RGB+D 2D	c-GAN	MMDa (CV)	0.365	# 3
Human action generation	NTU RGB+D 2D	c-GAN	MMDs (CV)	0.373	# 3

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	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/conditional-generative-adversarial-nets/human-action-generation-on-ntu-rgb-d)](https://paperswithcode.com/sota/human-action-generation-on-ntu-rgb-d?p=conditional-generative-adversarial-nets)`
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/conditional-generative-adversarial-nets/human-action-generation-on-ntu-rgb-d-2d)](https://paperswithcode.com/sota/human-action-generation-on-ntu-rgb-d-2d?p=conditional-generative-adversarial-nets)`

Conditional Generative Adversarial Nets

6 Nov 2014 · Mehdi Mirza, Simon Osindero ·

Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the conditional version of generative adversarial nets, which can be constructed by simply feeding the data, y, we wish to condition on to both the generator and discriminator. We show that this model can generate MNIST digits conditioned on class labels. We also illustrate how this model could be used to learn a multi-modal model, and provide preliminary examples of an application to image tagging in which we demonstrate how this approach can generate descriptive tags which are not part of training labels.

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MaximeVandegar/Papers-in-100-Lines-…

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znxlwm/pytorch-mnist-celeba-cgan-cd…

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mindspore-ai/models

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ImagingLab/Colorizing-with-GANs

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znxlwm/tensorflow-MNIST-cGAN-cDCGAN

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Human action generation

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Ranked #2 on Human action generation on NTU RGB+D 120

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Task	Dataset	Model	Metric Name	Metric Value	Global Rank	Benchmark
Human action generation	Human3.6M	c-GAN	MMDa	0.161	# 3	Compare
Human action generation	Human3.6M	c-GAN	MMDs	0.187	# 3	Compare
Human action generation	NTU RGB+D	c-GAN	FID (CS)	27.480	# 3	Compare
Human action generation	NTU RGB+D	c-GAN	FID (CV)	31.875	# 3	Compare
Human action generation	NTU RGB+D 120	c-GAN	FID (CS)	54.403	# 2	Compare
Human action generation	NTU RGB+D 120	c-GAN	FID (CV)	58.531	# 2	Compare
Human action generation	NTU RGB+D 2D	c-GAN	MMDa (CS)	0.334	# 3	Compare
			MMDs (CS)	0.354	# 3	Compare
			MMDa (CV)	0.365	# 3	Compare
			MMDs (CV)	0.373	# 3	Compare

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