Title: Muse: Text-To-Image Generation via Masked Generative Transformers From Google Research. ICML 2023. Highlight 作

Title: Autoregressive Image Generation without Vector Quantization From MIT. ArXiv 2024.06.17 Highlight 作者认为自回归图像生成模型中

Title: Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data From HKU & TikTok. CVPR 2024 Highlight 本

Title: Depth Anything V2 From HKU & TikTok. ArXiv 2024.06.13 Highlight 本文从分析最近的两个深度估计的工作Depth Aynthing V1和Diffusio

Title: Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models From PKU and No

Title: Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction From Bytedance Inc. ArXiv 20

Title: SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions From Xiaomi Inc. ArXiv 20240325 Highlig

Title: Clockwork Diffusion: Efficient Generation With Model-Step Distillation From Qualcomm AI Research. CVPR 2024. H

Title: SwiftBrush: One-Step Text-to-Image Diffusion Model with Variational Score Distillation From VinAI Research. CVPR

Title: CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image Generation From Google Research. C

Title: Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation From Stability AI. ArXiv 202

Title: Consistency Models From OpenAI, Yang Song. ICML 2023. Highlight 所谓的Consistency Models一致性模型，是约束在同一条PF ODE轨迹上的任意