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Research#llm📝 BlogAnalyzed: Dec 28, 2025 11:31

Render in SD - Molded in Blender - Initially drawn by hand

Published:Dec 28, 2025 11:05
1 min read
r/StableDiffusion

Analysis

This post showcases a personal project combining traditional sketching, Blender modeling, and Stable Diffusion rendering. The creator, an industrial designer, seeks feedback on achieving greater photorealism. The project highlights the potential of integrating different creative tools and techniques. The use of a canny edge detection tool to guide the Stable Diffusion render is a notable detail, suggesting a workflow that leverages both AI and traditional design processes. The post's value lies in its demonstration of a practical application of AI in a design context and the creator's openness to constructive criticism.
Reference

Your feedback would be much appreciated to get more photo réalisme.

Research#llm📝 BlogAnalyzed: Dec 24, 2025 20:10

Flux.2 vs Qwen Image: A Comprehensive Comparison Guide for Image Generation Models

Published:Dec 15, 2025 03:00
1 min read
Zenn SD

Analysis

This article provides a comparative analysis of two image generation models, Flux.2 and Qwen Image, focusing on their strengths, weaknesses, and suitable applications. It's a practical guide for users looking to choose between these models for local deployment. The article highlights the importance of understanding each model's unique capabilities to effectively leverage them for specific tasks. The comparison likely delves into aspects like image quality, generation speed, resource requirements, and ease of use. The article's value lies in its ability to help users make informed decisions based on their individual needs and constraints.
Reference

Flux.2 and Qwen Image are image generation models with different strengths, and it is important to use them properly according to the application.

Research#ImageGen🔬 ResearchAnalyzed: Jan 10, 2026 13:53

RealGen: Advancing Text-to-Image Generation with Detector-Guided Rewards

Published:Nov 29, 2025 12:52
1 min read
ArXiv

Analysis

The research on RealGen is promising, suggesting advancements in text-to-image generation through a novel detector-guided reward system. This approach likely improves image realism and coherence compared to previous methods.
Reference

RealGen utilizes detector-guided rewards for text-to-image generation.

GPT-4o Image Generation Update

Published:Mar 25, 2025 11:00
1 min read
OpenAI News

Analysis

This is a brief announcement highlighting the improved image generation capabilities of GPT-4o. It emphasizes the advancements over DALL·E 3, focusing on photorealism and image transformation.
Reference

4o image generation is a new, significantly more capable image generation approach than our earlier DALL·E 3 series of models. It can create photorealistic output. It can take images as inputs and transform them.