arXiv 2610.17227 · cs.CV · 2026-10-12
AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers
Javad Rajabi, Koorosh Roohi, David B. Lindell, Babak Taati
University of Toronto Computer Science
在最新榜 #217 本站收录于 2026-10-21
一句话要点
AReA 让扩散 Transformer 的注意力感受野随去噪步骤自适应收窄，更省算力地生成超高分辨率图像。
AReA adapts the attention receptive field across denoising steps so diffusion transformers generate beyond-training resolutions more cheaply.
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主题与学科
同主题：视觉生成
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数据说明
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