Image Enhancement And Relighting With Localized Control

AI image upscaler that hallucinates detail guided by text prompts.

Unique: Combines relighting and enhancement in a single operation using generative AI rather than traditional image processing filters. The approach allows for more natural-looking lighting adjustments than parametric controls, but sacrifices precision and predictability.

vs others: Offers one-click relighting that Photoshop and Lightroom require manual adjustment for; faster than traditional retouching but less controllable than parametric lighting tools.

via “relighting with preset-based illumination adjustment”

Stability AI's visual tool suite with removal, upscaling, and generation.

Unique: Implements relighting as a preset-based transformation rather than parameter-driven adjustment, suggesting a learned model that applies lighting changes end-to-end without exposing light direction, intensity, or color controls. This simplifies UX but limits customization compared to traditional lighting adjustment tools.

vs others: More accessible than manual lighting adjustment in Photoshop or Lightroom, but less flexible than parametric tools. Faster than professional retouching but may not match quality for critical product photography requiring precise lighting control.

via “relighting-aware image inpainting with spatial control”

IC-Light — AI demo on HuggingFace

Unique: Uses spatial conditioning maps as additional diffusion model inputs to encode lighting direction and mask information simultaneously, rather than simple concatenation or cross-attention approaches. This allows the model to generate inpainted content that inherently respects the scene's light source direction without post-processing.

vs others: Produces more photorealistic inpainting than generic diffusion inpainting tools (like Stable Diffusion inpaint) because it explicitly conditions on lighting geometry, reducing artifacts like inconsistent shadows or unnatural specular highlights.

via “selective adjustment with local masks”

via “adaptive product relighting”

via “lighting-enhancement-and-adjustment”

via “lighting-enhancement-simulation”

via “lighting-correction-and-enhancement”

via “image-inpainting-and-region-editing”

via “lighting and exposure adjustment”

via “professional lighting adjustment and enhancement”

via “lighting-and-exposure-enhancement”

via “skin tone preservation during enhancement”