SCALAR: Scale-wise Controllable Visual Autoregressive Learning

• URL: http://arxiv.org/abs/2507.19946v2
• Date: Tue, 29 Jul 2025 03:38:05 GMT
• Title: SCALAR: Scale-wise Controllable Visual Autoregressive Learning
• Authors: Ryan Xu, Dongyang Jin, Yancheng Bai, Rui Lan, Xu Duan, Lei Sun, Xiangxiang Chu,
• Abstract summary: We present SCALAR, a controllable generation method based on Visual Autoregressive ( VAR)<n>We leverage a pretrained image encoder to extract semantic control signal encodings, which are projected into scale-specific representations and injected into the corresponding layers of the VAR backbone.<n>Building on SCALAR, we develop SCALAR-Uni, a unified extension that aligns multiple control modalities into a shared latent space, supporting flexible multi-conditional guidance in a single model.
• Score: 15.775596699630633
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Controllable image synthesis, which enables fine-grained control over generated outputs, has emerged as a key focus in visual generative modeling. However, controllable generation remains challenging for Visual Autoregressive (VAR) models due to their hierarchical, next-scale prediction style. Existing VAR-based methods often suffer from inefficient control encoding and disruptive injection mechanisms that compromise both fidelity and efficiency. In this work, we present SCALAR, a controllable generation method based on VAR, incorporating a novel Scale-wise Conditional Decoding mechanism. SCALAR leverages a pretrained image encoder to extract semantic control signal encodings, which are projected into scale-specific representations and injected into the corresponding layers of the VAR backbone. This design provides persistent and structurally aligned guidance throughout the generation process. Building on SCALAR, we develop SCALAR-Uni, a unified extension that aligns multiple control modalities into a shared latent space, supporting flexible multi-conditional guidance in a single model. Extensive experiments show that SCALAR achieves superior generation quality and control precision across various tasks.

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