Loading / 加载中
A Reddit user shared a photorealistic interior image of a cozy gaming room. The study emphasized realistic lighting, natural clutter, and balanced RGB accents. The author offered to provide the prompt and workflow upon request. No specific model, benchmark, or novel technique was disclosed. The post exemplifies community-driven prompt engineering exploration rather than a formal release or breakthrough.
Researchers propose Elastic Diffusion Transformer (E-DiT), an adaptive framework to accelerate Diffusion Transformers by exploiting sample-dependent sparsity. Each DiT block is equipped with a lightweight router that dynamically decides to skip the block or reduce its MLP width. A training-free block-level feature caching mechanism further eliminates redundant computations. Experiments on Qwen-Image, FLUX, and Hunyuan3D-3.0 achieve up to ~2× speedup with negligible quality loss. Code and paper are publicly available.
A Reddit user introduced a technique to apply Krea 2's safety filter LoRA only on select parts of the image generation process, aiming to reduce the visible quality degradation caused by the filters. Inspired by a prior extraction of the filter's internal values, this approach shows some improvement in output but slows down generation. The optimal implementation and overall effectiveness remain uncertain.