CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Dec 20, 2024 · We begin our exploration with a comprehensive summary of existing efficient attention mechanisms and identify four key factors crucial for successful linearization of pre-trained DiTs: …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Dec 20, 2024 · The paper "CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up" addresses the computational challenges involved in generating high-resolution images using …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Dec 20, 2024 · This paper investigates how to convert a pre-trained Diffusion Transformer into a linear DiT, as its simplicity, parallelism, and efficiency for image generation are investigated, and proposes …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
This paper talks about CLEAR, a new method that improves the efficiency of Diffusion Transformers (DiTs) used for generating images by changing how they handle attention, which is the process of …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers ...
CLEAR：图像生成中的线性化革命 项目介绍 CLEAR （Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up）是一个针对预训练扩散变换器（DiT）的高效注意力机制研究项目。
扩散模型解读 (二十一)：CLEAR：类卷积线性扩散 Transformer
Jan 6, 2025 · Diffusion Transformer (DiT) 已经成为图像生成的主要架构。 然而，Self-Attention 的二次复杂度负责对 token 之间的关系进行建模，在生成高分辨率图像时会产生显著的时延。 为了解决这个 …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers ...
We begin our exploration with a comprehensive summary of existing efficient attention mechanisms and identify four key factors crucial for successful linearization of pre-trained DiTs: locality, formulation …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
In this paper, we present CLEAR, a convolution-like local attention strategy that effectively linearizes the attention mechanism in pre-trained Diffusion Transformers (DiTs), making them significantly more …
Daily Papers - Hugging Face
Mar 13, 2025 · Based on these insights, we introduce a convolution-like local attention strategy termed CLEAR, which limits feature interactions to a local window around each query token, and thus …
CLEAR/README.md at main · Huage001/CLEAR · GitHub
Based on these insights, we introduce a convolution-like local attention strategy termed CLEAR, which limits feature interactions to a local window around each query token, and thus achieves linear …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Dec 22, 2024 · The paper presents CLEAR, a novel convolution-like local attention mechanism that reduces the attention complexity of pre-trained Diffusion Transformers from quadratic to linear, …
CLEAR：图像生成中的线性化革命 - CSDN博客
Mar 29, 2025 · CLEAR（Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up）是一个针对预训练扩散变换器（DiT）的高效注意力机制研究项目。
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Dec 20, 2024 · The proposed CLEAR method uses a convolution-like local attention mechanism to linearize pre-trained diffusion transformers. This reduces computational complexity by 99.5% and …
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
CLEAR modifies the attention computation in diffusion transformers by introducing a linearized operation that approximates standard attention. The method uses a convolution-inspired approach to process …
Daily Paper Cast | CLEAR: Conv-Like Linearization Revs Pre-Trained ...
We begin our exploration with a comprehensive summary of existing efficient attention mechanisms and identify four key factors crucial for successful linearization of pre-trained DiTs: locality, formulation …