Core topics
Get direct help with the frustrating moments that interrupt an AI image or video workflow: unexplained edge artifacts, unexpected output, confusing format behavior, or a result that looks acceptable until it is exported. This question hub is for creators, ecommerce teams, and everyday users who want to understand…
A black background may come from Windows personalization or accessibility settings, or from lost image transparency. Identify where the black area appears, then follow the matching troubleshooting steps.
Preserve a person, character, or product’s identity by defining what cannot change, making one controlled edit at a time, and comparing each result with the original and approved…
Check identity, geometry, motion, temporal stability, framing, text, audio, provenance, rights, and delivery compatibility against a written acceptance brief.
Use the current tool's supported ratio and size, with enough real source detail for the subject and enough composition space for the intended motion.
AI video can crop a subject when the source ratio, destination frame, camera request, and available motion space do not agree.
AI video flicker comes from temporal inconsistency: colors, textures, edges, lighting, or object identity are regenerated differently across frames.
Faces can change because the model must synthesize new views and expressions over time from limited visible evidence while maintaining temporal consistency.
A plastic-looking upscale usually comes from aggressive denoising, invented texture, oversharpening, or repeated processing that removes natural variation.
AI upscaling can create plausible high-resolution detail and reduce some degradations, but it cannot prove what uncaptured detail originally looked like.
Automatic removal can cut off the subject when boundaries are ambiguous, contrast is weak, details are small, or a hard mask cannot represent partial transparency.