Fake It Till You Recognize It: Quality Assessment for Human Action Generative Models

Author:

Degardin Bruno1ORCID,Lopes Vasco2ORCID,Proença Hugo1ORCID

Affiliation:

1. Instituto de Telecomunicações, Aveiro, Portugal

2. DeepNeuronic, Covilhã, Portugal

Funder

FCT/MEC through National Funds

FEDER-PT2020 Partnership Agreement

FCT/MCTES through the National Funds and Co-Funded by EU Funds

‘Fundação para a Ciência e Tecnologia (FCT)’

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Reference61 articles.

1. How faithful is your synthetic data? Sample-level metrics for evaluating and auditing generative models;Alaa

2. A note on the inception score;Barratt;arXiv:1801.01973,2018

3. Demystifying MMD GANs;Bińkowski

4. Large scale GAN training for high fidelity natural image synthesis;Brock

5. Deep Video Generation, Prediction and Completion of Human Action Sequences

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