AI RESEARCH
SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation
arXiv CS.CV
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ArXi:2605.18267v1 Announce Type: new Normalizing flows (NFs) provide exact likelihoods and deterministic invertible sampling, but have historically lagged behind diffusion models for large-scale image generation. We identify a key obstacle: NFs are required to learn a single invertible transport over the full ambient space, making them highly sensitive to high-dimensional representations. This leads to a semantic-capacity mismatch in modern visual representation spaces, where semantic information is compact but encoded in overcomplete features. We propose SRC-Flow, which.