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Found 6 papers, 4 papers with code
FPGAN-Control: A Controllable Fingerprint Generator for Training with Synthetic Data
We demonstrate the merits of FPGAN-Control, both quantitatively and qualitatively, in terms of identity preservation level, degree of appearance control, and low synthetic-to-real domain gap.
Asymmetric Image Retrieval with Cross Model Compatible Ensembles
In this setting, a large model is used for indexing the gallery while a lightweight model is used for querying.
Synthetic Data for Model Selection
In contrast to using synthetic data for training, in this work we explore whether synthetic data can be beneficial for model selection.
GAN-Control: Explicitly Controllable GANs
We present a framework for training GANs with explicit control over generated images.
Dynamic-Net: Tuning the Objective Without Re-training for Synthesis Tasks
Our approach considers an "objective-space" as the space of all linear combinations of two objectives, and the Dynamic-Net is emulating the traversing of this objective-space at test-time, without any further training.
Adversarial Feedback Loop
In this paper we propose a novel method that makes an explicit use of the discriminator in test-time, in a feedback manner in order to improve the generator results.
