Adobe Lightroom Classic 12.3 Jun 2026
Adds contrast and structure specifically to facial hair.
Moving beyond the legacy Spot Removal tool’s healing and cloning, Lightroom Classic 12.3 introduced a new "Content-Aware Remove" mode as a technology preview. Instead of sampling a user-selected source point, the AI analyzes surrounding pixel data to intelligently fill the selected area. While not perfect for complex patterns, it proved remarkably effective for removing dust spots, sensor debris, wires, and small blemishes without manual source selection.
: AI masking now includes specific options for Facial Hair and Clothes , making portrait retouching much faster . Interface and Workflow Improvements New in Adobe Lightroom Classic 12.3 - AI Denoise
Analyzes the image automatically, minimizing the need for complex manual slider adjustments. How to Use AI Denoise Adobe Lightroom Classic 12.3
I can provide tailored settings to make your Lightroom catalog run as fast as possible.
: The AI masking for people was expanded to include specific selections for facial hair UI Indicators : Adobe replaced panel switches with "eye" icons
Adjust specific tonal ranges (shadows, midtones, highlights) within just the background or just the subject. Adds contrast and structure specifically to facial hair
Boosts texture and vibrancy on apparel while leaving the subject's skin untouched.
Automatically enhances skin, teeth, and eyes in one click.
You can now use the Tone Curve tool within specific masks for precise local contrast control. While not perfect for complex patterns, it proved
This guide covers the full scope of Lightroom Classic 12.3. If you need deeper details on any module or new 12.3 feature, just ask.
This isn't just an incremental improvement. According to Adobe, Denoise uses advanced artificial intelligence to efficiently remove noise from RAW images while preserving all the crisp details that make a photo stand out. It’s a step beyond the traditional "Luminance" and "Color" sliders in the Detail panel, which often struggle to distinguish between noise and fine texture.