The paper introduces HiCo, a hierarchical controllable diffusion model that enables precise layout‑to‑image generation by decoupling object and background features through weight‑shared branches and a fusion module, achieving high‑quality results and efficient inference as demonstrated on the HiCo‑7K benchmark.
This article introduces Alibaba Cloud's AI painting solution, showcases creative use cases, explains the underlying model architecture, and provides a step‑by‑step tutorial for deploying the service on ECS with DashScope in just a few minutes.
This article reviews the evolution from GANs to diffusion models, explains the components of Stable Diffusion—including the CLIP text encoder, VAE, and UNet—and provides step‑by‑step Python code using HuggingFace's Diffusers library to generate images from text prompts.
This tutorial explains how to use PHP to connect to Midjourney's AI painting API, covering preparation, request construction, cURL transmission, response handling, and a complete example that enables developers to generate and manage AI‑created artwork.
AI painting leverages deep‑learning models to analyze and recreate color palettes, enabling machines to mimic famous artists, generate novel hues, and express emotions, while also facing challenges such as limited creativity, human‑AI interaction, and fine‑detail rendering.
This article explores the rapid rise of AI painting tools such as Midjourney and Stable Diffusion, compares their features, outlines new design workflows, and presents four detailed case studies—from 2D‑to‑3D character creation to poster and H5 header generation—showing how designers can boost productivity and creativity.
QQGC, Tencent’s two‑stage text‑to‑image model that separates CLIP‑based Prior mapping from a Stable Diffusion Decoder, leverages T5‑enhanced text embeddings and a suite of efficiency tricks—including FP16, flash attention, ZeRO and GPU‑RDMA—to train over‑2 B‑parameter models on 64 GPUs, achieving state‑of‑the‑art FID and CLIP scores while supporting image variation, semantic img2img, precise CLIP‑vector edits and unsafe‑content filtering, and now powers the company’s Magic Painting Room.
This article analyzes Baidu’s ERNIE‑ViLG 2.0 and PaddlePaddle‑optimized Stable Diffusion models, presenting benchmark comparisons, hardware‑specific speed and memory gains, and the underlying inference optimizations that enable low‑cost, high‑throughput AI‑generated image creation.
