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MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation.

, , , and . CVPR, page 8036-8045. Computer Vision Foundation / IEEE, (2020)

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FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery., , and . CoRR, (2018)MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation., , , and . CVPR, page 8036-8045. Computer Vision Foundation / IEEE, (2020)FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery., , and . CVPR, page 6490-6499. Computer Vision Foundation / IEEE, (2019)Generating Furry Cars: Disentangling Object Shape and Appearance across Multiple Domains., , and . ICLR, OpenReview.net, (2021)Denoising High Resolution Multispectral Images Using Deep Learning Approach., and . ICMLA, page 871-875. IEEE Computer Society, (2016)Few-Shot Image Generation via Cross-Domain Correspondence., , , , , , and . CVPR, page 10743-10752. Computer Vision Foundation / IEEE, (2021)NAG: Network for Adversary Generation., , , and . CVPR, page 742-751. Computer Vision Foundation / IEEE Computer Society, (2018)Yo'LLaVA: Your Personalized Language and Vision Assistant., , , , , and . CoRR, (2024)Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data., , , and . NeurIPS, (2020)Towards Universal Fake Image Detectors that Generalize Across Generative Models., , and . CVPR, page 24480-24489. IEEE, (2023)