DSS-GAN: Directional State Space GAN with Mamba backbone for Class-Conditional Image Synthesis
We present DSS-GAN, the first generative adversarial network to employ Mamba as a hierarchical generator backbone for noise-to-image synthesis. The central contribution is Directional Latent Routing (DLR), a novel conditioning mechanism that decomposes the latent vector into direction-specific subvectors, each jointly projected with a class embedding to produce a feature-wise affine modulation of the corresponding Mamba scan. Unlike conventional class conditioning that injects a global signal, DLR couples class identity and latent structure along distinct spatial axes of the feature map, applied consistently across all generative scales. DSS-GAN achieves improved FID, KID, and precision-r...
| Authors | Aleksander Ogonowski, Konrad Klimaszewski, Przemysław Rokita |
|---|---|
| Primary category | cs.LG |
| Published | 18 March 2026 |
| Last updated at source | 18 March 2026 |
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