Unverified75% confidenceFactTime unknown
Veo采用了级联扩散模型（Cascaded Diffusion Models）架构，先在低分辨率空间生成语义骨架，再逐步上采样至高分辨率
1
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75%
Confidence
Long-term
Relevance
5/31/2026
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UnverifiedThe multi-stage Cascaded Diffusion Model architecture first generates the overall composition at low resolution, then progressively upscales it through super-resolution networks to supplement high-frequency details.72% similarUnverified扩散模型推理速度较慢，通常需要数十步去噪迭代才能生成一张图像，这催生了DDIM、DPM-Solver等加速采样算法63% similarVerified扩散模型以 DALL-E 2、Stable Diffusion、Midjourney 为代表，重新定义了图像生成任务63% similarVerifiedStable Diffusion is based on the Latent Diffusion Model and generates high-quality images by performing a denoising process in a compressed latent space62% similarUnverifiedStable Diffusion 基于去噪扩散概率模型（DDPM）理论，将扩散过程从像素空间转移到低维潜在空间，由VAE负责编解码，CLIP模型将文本提示编码为语义向量61% similar
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