Visual Autoregressive Scalable Image Generation Via Next Scale Prediction 2025 Forecast. GitHub FoundationVision/VAR [NeurIPS 2024 Best Paper][GPT beats diffusion🔥] [scaling laws in of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction" Results suggest VAR has initially emulated the two important properties of LLMs: Scaling Laws and zero-shot task generalization, and it is empirically verified that VAR outperforms the Diffusion Transformer in multiple dimensions including image quality, inference speed, data efficiency, and scalability
Paper page Visual Autoregressive Modeling Scalable Image Generation via NextScale Prediction from huggingface.co
We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next. 4.1 State-of-the-art image generation; 4.2 Power-law scaling laws; 4.3 Zero-shot task generalization; 4.4 Ablation Study; 5 Future Work; 6 Conclusion; A Token.
Paper page Visual Autoregressive Modeling Scalable Image Generation via NextScale Prediction
[NeurIPS 2024 Best Paper][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction" Results suggest VAR has initially emulated the two important properties of LLMs: Scaling Laws and zero-shot task generalization, and it is empirically verified that VAR outperforms the Diffusion Transformer in multiple dimensions including image quality, inference speed, data efficiency, and scalability
Paper Review Visual Autoregressive Modeling Scalable Image Generation via NextScale. Visual-AutoRegressive Modeling via Next-Scale Prediction Results suggest VAR has initially emulated the two important properties of LLMs: Scaling Laws and zero-shot task generalization, and it is empirically verified that VAR outperforms the Diffusion Transformer in multiple dimensions including image quality, inference speed, data efficiency, and scalability
Paper Review Visual Autoregressive Modeling Scalable Image Generation via NextScale. approach begins by encoding an image into multi-scale token maps.The autoregressive process is then started from the 1×1 token map, and progressively expands in resolution: at each step, the transformer predicts the next higher-resolution token map conditioned on all previous ones. 4.1 State-of-the-art image generation; 4.2 Power-law scaling laws; 4.3 Zero-shot task generalization; 4.4 Ablation Study; 5 Future Work; 6 Conclusion; A Token.