Artifacts (Visual)
What is Artifacts (Visual)?
Visual artifacts are unwanted glitches or errors that appear in an image or video: things that shouldn't be there, like blurry patches, weird textures, or extra fingers on a hand.
At a glance
- Also known as
- GlitchesVisual glitchesCompression artifactsGeneration errors
- Used for
- Identifying quality issues in AI outputPost-production cleanupModel evaluation
- Common tools
- Topaz video AIAdobe after effectsRunwayDaVinci resolve
- Related terms
- CompressionDiffusion modelInpaintingUpscalingTemporal consistency
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How it compares
Compression artifacts are caused by data reduction algorithms and appear as predictable, mathematically patterned distortions such as blocks or ringing. Generation artifacts arise from the probabilistic nature of AI models and are less predictable, often manifesting as anatomical errors, hallucinated details, or temporal inconsistencies in video.
Think of it like…
Think of visual artifacts like mistakes a very fast, very confident artist makes when painting from memory. They know roughly what a hand looks like, so they paint one: but under pressure they might add an extra finger or make the proportions slightly wrong. The painting looks almost right at a glance, but something is clearly off on closer inspection.
Pro tip
When reviewing AI video output for artifacts, play the footage at half speed and look specifically at edges, hands, and any text present in the scene: these areas are statistically the most likely to contain generation errors and temporal inconsistencies.
Types and variations
- Compression artifacts occur when lossy codecs discard visual data, resulting in blockiness, ringing, or colour banding.
- Generation artifacts are specific to AI models and include anatomical errors (malformed hands, merged faces), hallucinated text, and incoherent backgrounds.
- Temporal artifacts appear in video and manifest as flickering, frame-to-frame inconsistency, or ghosting.
- Semantic artifacts are logically incorrect elements: a clock showing an impossible time or a sign with scrambled letters: that are visually plausible but factually wrong.
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Try MorphicCommon use cases
- Visual artifacts must be managed any time AI-generated content is used in a professional context.
- In AI video production, practitioners review output for temporal flickering and anatomical errors before delivery.
- In image generation workflows, artifacts around hands, eyes, and text are routinely fixed using inpainting or re-generation.
- In archival and restoration work, older compression artifacts in legacy footage are addressed using AI upscalers and denoisers.
- Quality assurance pipelines for generative tools often include automated artifact detection to flag frames that require human review.
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FAQs
They are caused by the probabilistic nature of generative models. Because these models learn statistical patterns from training data rather than understanding geometry or physics, they can produce plausible-looking but incorrect details, especially in complex areas like hands, faces, or text.
Not exactly. Compression artifacts are a specific type caused by lossy data encoding, resulting in blockiness or banding. AI generation artifacts are broader and include anatomical errors, hallucinated content, and frame-to-frame inconsistencies in video.
Common approaches include increasing the number of inference steps during generation, using higher-quality base models, applying temporal consistency tools, and using post-processing software such as Topaz Video AI to clean up the output.
Hands are anatomically complex and highly variable in appearance across training images. The model must predict the exact number and position of fingers from context, which is a difficult inference problem that current models frequently get wrong.
Many artifacts can be reduced or eliminated using inpainting, upscaling, denoising, or manual compositing. However, severe temporal artifacts in video or major anatomical errors may require regenerating the affected content entirely.
Not necessarily. Even state-of-the-art models produce artifacts under certain conditions, particularly with unusual prompts or edge-case content. Artifact frequency and severity are useful metrics for comparing models, but some degree of error is present in all current generative systems.
A temporal artifact is an inconsistency that occurs across frames rather than within a single frame. Examples include flickering textures, objects that change shape between frames, or lighting that shifts unnaturally from one moment to the next.
