3 papers
cs.CV2026
Just-in-Time: Training-Free Spatial Acceleration for Diffusion Transformers
Wenhao Sun, Ji Li, Zhaoqiang Liu
Diffusion Transformers have established a new state-of-the-art in image synthesis, but the high computational cost of iterative sampling severely hampers their practical deployment…
cs.CV2025
MMMG: A Massive, Multidisciplinary, Multi-Tier Generation Benchmark for Text-to-Image Reasoning
Yuxuan Luo, Yuhui Yuan, Junwen Chen +6
In this paper, we introduce knowledge image generation as a new task, alongside the Massive Multi-Discipline Multi-Tier Knowledge-Image Generation Benchmark (MMMG) to probe the rea…
cs.CV2025
ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation
Yifan Pu, Yiming Zhao, Zhicong Tang +14
Multi-layer image generation is a fundamental task that enables users to isolate, select, and edit specific image layers, thereby revolutionizing interactions with generative model…