Visual Autoregressive Scalable Image Generation Via Next Scale Prediction 2025 Forecast

Visual Autoregressive Scalable Image Generation Via Next Scale Prediction 2025 Forecast. [PDF] Autoregressive Model Beats Diffusion Llama for Scalable Image Generation Semantic Scholar We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next-scale prediction" or "next-resolution prediction", diverging from the standard raster-scan "next-token prediction" 馃敟 Introducing VAR: a new paradigm in autoregressive visual generation : Visual Autoregressive Modeling (VAR) redefines the autoregressive learning on images as coarse-to-fine "next-scale prediction" or "next-resolution prediction", diverging from the standard raster-scan "next-token prediction".

Figure 2 from Exploring Stochastic Autoregressive Image Modeling for Visual Representation
Figure 2 from Exploring Stochastic Autoregressive Image Modeling for Visual Representation from www.semanticscholar.org

[NeurIPS 2024 Best Paper][GPT beats diffusion馃敟] [scaling laws in visual generation馃搱] Official impl 3 Method 3.1 Preliminary: autoregressive modeling via next-token prediction

Figure 2 from Exploring Stochastic Autoregressive Image Modeling for Visual Representation

We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines. We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next. The VAR framework reconceptualizes the autoregressive modeling on images by shifting from next-token prediction to next-scale prediction approach, a process under which instead of being a single token, the autoregressive unit is an entire token map.

Exploring Stochastic Autoregressive Image Modeling for Visual Representation DeepAI. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction" Visual-AutoRegressive Modeling via Next-Scale Prediction

Visual Autoregressive Modeling Scalable Image Generation via NextScale Prediction Papers. 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 We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next.