# Visual Autoregressive Modeling for Image Super-Resolution

arXiv: https://arxiv.org/abs/2501.18993 · HTML: https://mlsanity.com/paper/2501.18993/

## Key facts

- Cited by 36 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jan 2025.

## Built on by (most cited first, 30 of 36)

- [The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report](https://mlsanity.com/paper/2504.10686/) (2025)
- [SCALAR: Scale-wise Controllable Visual Autoregressive Learning](https://mlsanity.com/paper/2507.19946/) (2025)
- [RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration](https://mlsanity.com/paper/2505.18047/) (2025)
- [Semantic Context Matters: Improving Conditioning for Autoregressive Models](https://mlsanity.com/paper/2511.14063/) (2025)
- [RealSR-R1: Reinforcement Learning for Real-World Image Super-Resolution with Vision-Language Chain-of-Thought](https://mlsanity.com/paper/2506.16796/) (2025)
- [Progressive Supernet Training for Efficient Visual Autoregressive Modeling](https://mlsanity.com/paper/2511.16546/) (2025)
- [Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression](https://mlsanity.com/paper/2604.10546/) (2026)
- [Self-Evolving Agentic Image Restoration via Deliberate Planning and Intuitive Execution](https://mlsanity.com/paper/2606.28971/) (2026)
- [TanDiT: Tangent-Plane Diffusion Transformer for High-Quality 360deg Panorama Generation](https://mlsanity.com/paper/2506.21681/) (2025)
- [Texture Vector-Quantization and Reconstruction Aware Prediction for Generative Super-Resolution](https://mlsanity.com/paper/2509.23774/) (2025)
- [GenAR: Next-Scale Autoregressive Generation for Spatial Gene Expression Prediction](https://mlsanity.com/paper/2510.04315/) (2025)
- [ProGVC: Progressive-based Generative Video Compression via Auto-Regressive Context Modeling](https://mlsanity.com/paper/2603.17546/) (2026)
- [ScaleWeaver: Weaving Efficient Controllable T2I Generation with Multi-Scale Reference Attention](https://mlsanity.com/paper/2510.14882/) (2025)
- [Markovian Scale Prediction: A New Era of Visual Autoregressive Generation](https://mlsanity.com/paper/2511.23334/) (2025)
- [Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset](https://mlsanity.com/paper/2603.04745/) (2026)
- [Multi-scale Image Super Resolution with a Single Auto-Regressive Model](https://mlsanity.com/paper/2506.04990/) (2025)
- [HSI-VAR: Rethinking Hyperspectral Restoration through Spatial-Spectral Visual Autoregression](https://mlsanity.com/paper/2602.00749/) (2026)
- [Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis](https://mlsanity.com/paper/2602.01345/) (2026)
- [VARestorer: One-Step VAR Distillation for Real-World Image Super-Resolution](https://mlsanity.com/paper/2604.21450/) (2026)
- [Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution](https://mlsanity.com/paper/2605.23264/) (2026)
- [HACK++: Towards More Effective Head-Aware Key-Value Compression for Efficient Visual Autoregressive Modeling](https://mlsanity.com/paper/2606.08302/) (2026)
- [AlignVAR: Towards Globally Consistent Visual Autoregression for Image Super-Resolution](https://mlsanity.com/paper/2603.00589/) (2026)
- [StepVAR: Structure-Texture Guided Pruning for Visual Autoregressive Models](https://mlsanity.com/paper/2603.01757/) (2026)
- [UHD Image Deblurring via Autoregressive Flow with Ill-conditioned Constraints](https://mlsanity.com/paper/2603.10517/) (2026)
- [HeatKV: Head-tuned KV-cache Compression for Visual Autoregressive Modeling](https://mlsanity.com/paper/2605.14877/) (2026)
- [Masked Next-Scale Prediction for Self-supervised Scene Text Recognition](https://mlsanity.com/paper/2605.14885/) (2026)
- [Hierarchical Image Tokenization for Multi-Scale Image Super Resolution](https://mlsanity.com/paper/2605.14891/) (2026)
- [HiTokSR: A Coarse-to-Fine Tokenizer with Hierarchical Codebooks for High-Fidelity Real-World Image Super-Resolution](https://mlsanity.com/paper/2606.01157/) (2026)
- [Next-Dense-Stride Prediction for Multimodal Autoregressive Visual Modeling](https://mlsanity.com/paper/2607.09892/) (2026)
- [Structure-Detail Decoupled Autoregressive Generation for Fast and High-Fidelity Virtual Try-On](https://mlsanity.com/paper/2607.11233/) (2026)

## Abstract (arXiv)

Image Super-Resolution (ISR) has seen significant progress with the introduction of remarkable generative models. However, challenges such as the trade-off issues between fidelity and realism, as well as computational complexity, have also posed limitations on their application. Building upon the tremendous success of autoregressive models in the language domain, we propose VARSR, a novel visual autoregressive modeling for ISR framework with the form of next-scale prediction. To effectively integrate and preserve semantic information in low-resolution images, we propose using prefix tokens to incorporate the condition. Scale-aligned Rotary Positional Encodings are introduced to capture spatial structures and the diffusion refiner is utilized for modeling quantization residual loss to achieve pixel-level fidelity. Image-based Classifier-free Guidance is proposed to guide the generation of more realistic images. Furthermore, we collect large-scale data and design a training process to obtain robust generative priors. Quantitative and qualitative results show that VARSR is capable of generating high-fidelity and high-realism images with more efficiency than diffusion-based methods. Our codes will be released at https://github.com/qyp2000/VARSR.