Consistent Character Generation

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Most implemented papers archive 2025-07-28

6 shown of 6 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• CharaConsist: Fine-Grained Consistent Character Generation
  15 Jul 2025 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  In text-to-image generation, producing a series of consistent contents that preserve the same identity is highly valuable for real-world applications.
• Character-Adapter: Prompt-Guided Region Control for High-Fidelity Character Customization
  24 Jun 2024 1 repository listed
  Customized image generation, which seeks to synthesize images with consistent characters, holds significant relevance for applications such as storytelling, portrait generation, and character design.
• Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior
  7 Jun 2024 1 repository listed
  This enables a greater number of cross-frame attentions over more frames within the same computational budget, thereby enhancing both video quality and temporal coherence.
• CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models
  24 Apr 2024 1 repository listed Syntology ran 7 of 9 samples · 2 unverified
  In this work, we propose CharacterFactory, a framework that allows sampling new characters with consistent identities in the latent space of GANs for diffusion models.
• CAT: Contrastive Adapter Training for Personalized Image Generation
  11 Apr 2024 1 repository listed
  Finally, we mention the possibility of CAT in the aspects of multi-concept adapter and optimization.
• The Chosen One: Consistent Characters in Text-to-Image Diffusion Models
  16 Nov 2023 1 repository listed
  Recent advances in text-to-image generation models have unlocked vast potential for visual creativity.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.