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DMA$^2$: Pixel-space Distribution Matching with Adversarial and Anchor Losses

Paper recorded by Signals 4 on 2026-09-29 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-29 on arXiv · recorded by Signals 4 on 2026-09-30

Category: cs.CV · 计算机视觉 · first seen 2026-09-30

Abstract

Distribution matching distillation (DMD) provides a general framework for few-step diffusion generation, but its modern text-to-image instantiations have been developed primarily around latent diffusion. It therefore overlooks key properties and design opportunities of native RGB. We revisit two DMD interfaces for pixel-space teachers. On the teacher-matching side, diagnostics show low-noise RGB m

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#5 most recent of 357 cs.CV papers we have recorded · ↑ newer: Rethinking Representations for World-Action Modeling · ↓ older: LongLive-Plug: Once-for-All Distillation for Video Generation
Cite this page: DMA$^2$: Pixel-space Distribution Matching with Adversarial and Anchor Losses: the #5 most recent of 357 cs.CV papers we have recorded (as of 2026-09-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/dma-2-pixel-space-distribution-matching-with-adversarial-and-anchor-losses.html
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