What AI Does Well (and Poorly) for Photo Generation — Especially People & Consistency

Where AI image generation shines, where it struggles — particularly with people — and how to get consistent identities across many images.

Written By Arina

Last updated About 1 month ago

TL;DR

AI is excellent at single-subject portraits, mood/lighting, composition, and broad body/wardrobe styling. It is weaker at anatomy edge cases (hands/feet), small text/logos, accessories, reflections, and keeping the same face perfectly consistent across angles and sessions. You can overcome most weaknesses with the right prompting, LoRA choices, Reference-To-Image/Variations/Photoshoot flows, Image Upscaler, and by running Head & Face Swap last to lock identity.

What AI is Good At

  • Photoreal mood and lighting. Natural window light, golden hour, studio key/rim setups, soft shadows, shallow depth of field, filmic grades.

  • Single-person portraits. Headshots and 3/4 portraits with clean backgrounds and clear facial features.

  • Composition & camera "feel." 35/50/85mm looks, low/high angles, center vs. rule-of-thirds framing.

  • Broad styling. Body-shape trends, wardrobe categories, hair length/texture, makeup styles.

  • Aesthetic replication. Matching a visual vibe from a reference (color grade, lighting, lens feel) using Reference-To-Image or the Variations tool.

  • Batch variety. Producing cohesive sets of similar images in one go (Variations, Photoshoot).

  • In-image text. Signs, posters, and captions — but only with the right model (Nano Banana 2 is the one built for this; most others render gibberish).

  • Precise physique/style control. SDXL Body-Shape LoRAs (Text to Image, Reference-To-Image) and Flux Klein Style LoRAs (Image Editor) both give reliable, repeatable control that plain prompting can't match.

Where AI Struggles (and Why)

  • Identity consistency across angles/time. The same person can drift in side profiles, extreme expressions, or new scenes.

  • Hands, feet, and fine anatomy. Fingers may merge, grips look awkward, toes warp in sandals; extreme muscularity can look plasticky.

  • Small text/logos and micro-details on any model other than Nano Banana 2 — tiny jewelry patterns, watch faces, signage.

  • Accessories & occlusions. Glasses frames, earrings behind hair, hair crossing the face, hats touching eyebrows, hands near the mouth.

  • Reflections and translucency. Mirrors, glass, water surfaces; lens reflections on glasses.

  • Complex pattern geometry. Tight stripes, checks, lace meshes, and detailed embroidery.

  • Multi-person interactions. Eye-lines, hand placement, scale/perspective consistency among several people.

  • Exact brand replication or copyrighted marks. Models tend to avoid precise logos; results can be off or garbled.

Getting Consistent People: Proven Strategies

1) Be explicit about the person

Describe face cues (eye color/shape, brow fullness/arch, nose bridge/width, lip fullness/shape, jawline/cheekbones, freckles/moles, facial hair), hair cues (length, texture, parting, color), age band, and body type. This improves both generation and Image Upscaler results.

2) Use the right tool at the right moment

  • Face Generation to craft candidate faces quickly.

  • Text to Image for new looks/poses — choose the model based on your priority (see the model breakdown below).

  • Reference-To-Image when you need the same vibe, angle family, or outfit line as an example image.

  • Photoshoot to create multi-category sets (office/café/vacation…) while preserving identity.

  • Variations for rapid, on-theme variations around your best hero shot.

  • Image Upscaler to lift detail/resolve softness. Use Safe Face variants if the face must remain unchanged.

  • Head & Face Swap (last step) to lock identity across everything you'll publish.

3) Picking a model: what each one is actually good at

Text to Image and Image Editor both offer a range of models — there's no single "best" one, it depends on what you're optimizing for:

  • General — highest overall quality, 4K, great for keeping the same face across a character series.

  • Nano Banana 2 — the most photorealistic option for clean SFW work, and the only model that reliably renders in-image text.

  • Seedream 5 / Seedream 5 Pro — strong prompt understanding and stylization; Pro adds the widest aspect-ratio support and highest fidelity.

  • Qwen Image / Qwen Image Pro — aesthetic, good likeness, few artifacts; Pro adds realism.

  • WAN 2.7 Image / WAN 2.7 Pro — precise editing and composition with fewer hand/limb artifacts than older models.

  • SDXL — the one that supports Body-Shape LoRAs, for when physique/proportions matter more than raw realism.

  • Flux Klein Spicy / Flux Klein LoRA — built for full NSFW content, including style-template LoRAs.

If realism slips on any model, try lowering LoRA strengths (if used), simplifying the prompt, or switching models — then end with Head & Face Swap to lock the face.

4) LoRAs without chaos

ZenCreator has two different kinds of LoRAs — see the full LoRA Guide for both:

  • SDXL Body-Shape LoRAs (Text to Image, Reference-To-Image) — use 1–2 at 0.6–0.9 each; 0.8 is a great starting point. Combining 3 is fine, but keep strengths conservative and avoid contradictions (e.g., Slim Figure vs. Plus Size Body). Over 1.5 increases artefacts (warping, crunchy textures) — if detail drops or anatomy breaks, lower strengths by 0.2 and simplify the prompt.

  • Flux Klein Style LoRAs (Image Editor) — style templates: upload a photo and the LoRA transforms it to match the template. One at a time; results follow the template's composition.

5) Keep the scene "stable"

  • Reuse lighting language, camera terms (e.g., "50mm, eye-level, shallow DOF"), and grade cues across the whole set.

  • Avoid changing too many variables at once (pose, outfit, environment, lighting) if identity is your priority.

6) Pipeline that works

Generate → pick winners → Image Upscaler (or a Safe Face variant if identity must not change) → Head & Face Swap (final) → optional color LUT/grain → publish.

If you need big batches, run Head & Face Swap only on selects to save credits/time.

Prompting for People (Quick Reminders)

  • Write in this order: person → body/wardrobe → pose/camera → lighting → environment → mood/grade → quality.

  • Keep the negative prompt lean but targeted:

    lowres, bad anatomy, extra limbs, deformed hands, fused fingers, duplicate face, blurry, over-smooth skin, watermark, text, jpeg artifacts, harsh sharpening

  • Use Magic Prompt (in Text to Image) if you're not sure how to phrase it — it expands a short idea into a full, detailed prompt automatically.

See the full guide "How to Write Prompts".

Common Failure Modes and Fixes

Face changes between slides: reuse the same aspect ratio; end with Head & Face Swap.

Hands look wrong: simplify pose; add bad hands to negatives; avoid extreme wide-angle; re-generate close-ups separately.

Soft/"plastic" skin: reduce LoRA strengths; add "realistic skin texture, natural pores"; finish with Image Upscaler.

Weird glasses/earrings: remove from the initial prompt; add later via Head & Face Swap into a base where the face is already stable.

Hair inconsistency: specify length, parting, and texture; keep lighting/camera the same across the set.

Reflections look fake: avoid mirrors/wet glass in generation; composite later or choose angles without reflections.

Tiny logos/text garbled: switch to Nano Banana 2, or add in post if brand marks are critical.

Over-muscular or distorted physiques: lower body-shape LoRA strength; add "realistic anatomy, proportional limbs" to the prompt.

Quality Bars Before You Publish

  • The same person is recognizable in front, 3/4, and mild profile views.

  • Hair is the same length/texture/parting across the set.

  • Eyes are aligned; no extra reflections, no duplicated catchlights.

  • Hands and fingers are plausible; no fused digits.

  • Clothing behaves like real fabric; seams and edges look natural.

  • Lighting and grade feel consistent; no jarring clip/crush.

  • Resolution meets platform spec; use Image Upscaler where needed.

  • Final step was Head & Face Swap (unless you used a Safe Face upscale and identity was perfect already).

Practical Playbooks

  • New virtual persona: Face Generation → pick a hero → Text to Image/Reference-To-Image to build range → Image Upscaler → Head & Face Swap last.

  • Real person look-alike: generate a base scene → Head & Face Swap last with the authorized source portrait → quick color pass → publish.

  • Large campaign set: Photoshoot per category → schedule posts.

Final Notes

LoRA keywords are added automatically when you pick a SDXL Body-Shape LoRA — keep your text readable and focused on the shot.

If you need a bigger image but the face must remain untouched, use a Safe Face Image Upscaler variant.

If identity is the contract, Head & Face Swap is your safety net — run it last.

When in doubt, generate small, review anatomy/identity, then scale up your batch.

Need help choosing the right flow for your project? Ping the chat bubble or email support@zencreator.com.