Touch of Realism [SDXL]

https://civitai.com/models/1705430/touch-of-realism-sdxl?modelVersionId=1934796

(Optional additions to your prompt:)

foreground blur [object] catching the sunlight natural light from the side soft foreground lens softness realistic depth falloff cinematic shallow DOF bokeh in the distance soft focus edges

LoRA name: lora:Touch_of_Realism_SDXL_V2 Trigger word: touch-of-realismV2

Touch of Realism V2 is a subtle style LoRA trained on my own Sony A7III photography, using a 100–400mm telephoto and 30mm wide-angle lens. It enhances your SDXL generations with a more photographic look: smoother lighting, better depth separation, sharper subject detail, and a touch of natural lens softness.

My new SDXL checkpoint, HuslyoRealismXL, already has this LoRA baked in. Give it a try!

Consistent characters Want to create consistent AI characters and follow a tested photorealistic workflow in Automatic1111? Join my private Discord via Fanvue! Get full access to my consistent character LoRA workflow, Instagram model creator workflow and prompt packs.

My Fanvue page: → https://www.fanvue.com/huslyo123/fv-3 More info: https://huslyo123.carrd.co/

This LoRA is ideal for anyone looking to add realism and lens-based aesthetics to portraits, animals, plants, NSFW imagery, or natural scenes. It brings cinematic softness, organic depth transitions, and occasional background bokeh or optical blur that mimics real lens behavior. It works best at a strength of 0.5 for subtle enhancement without overpowering your base prompt.

✦ Adds: realistic focus falloff around the edges, soft light flares in the highlights, and a shallow depth of field effect that gives your subject natural separation without looking artificial.

✦ Best used with: portraits, macro photography, wildlife scenes, atmospheric landscapes, photorealistic compositions, and sensual or NSFW imagery in natural lighting.

The V2 version offers a slightly stronger effect and was trained on a more refined dataset, resulting in more consistent and satisfying output across a variety of prompt styles.