3 citations · 8 across the 10 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.CV2024★ 3 cited
-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers
Pengtao Chen, Mingzhu Shen, Peng Ye +5
Diffusion models are widely recognized for generating high-quality and diverse images, but their poor real-time performance has led to numerous acceleration works, primarily focusi…
cs.CV2024★ 2 cited
ClipSAM: CLIP and SAM Collaboration for Zero-Shot Anomaly Segmentation
Shengze Li, Jianjian Cao, Peng Ye +3
Recently, foundational models such as CLIP and SAM have shown promising performance for the task of Zero-Shot Anomaly Segmentation (ZSAS). However, either CLIP-based or SAM-based Z…