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AI video generation: LoRA training vs. depth maps for consistency

A user on Reddit is seeking advice on improving the consistency of AI-generated product photography videos using less expensive models. They are comparing two potential methods: training a LoRA model or using more accurate grayscale depth map reference videos. The goal is to achieve better object consistency, especially during object rotations, which current cheaper models like Seedance 1.5, Grok Imagine, or WAN 2.2 fail to do effectively. AI

IMPACT Users are exploring methods to improve AI video generation consistency with more accessible models.

RANK_REASON User is asking for advice on a technical approach to improving AI model output, not reporting on a new release or significant industry event.

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/GrapefruitForeign ·

    training a lora model VS using motion control grayscale depth reference video

    <!-- SC_OFF --><div class="md"><p>I have a video gen usecase, its product photography videos in a specific niche</p> <p>when I use more expensive models it mostly works perfectly, and now with the models like gemini omni its getting even better (tho thats not out in api so i cant…