PromptCCD uses Gaussian Mixture Prompts for global class prototypes and PromptCCD++ adds part-level prompt pools for finer representations in continual category discovery from unlabeled streams.
In: NeurIPS (2017)
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Refinement via Regeneration (RvR) reformulates image refinement in unified multimodal models as conditional regeneration using prompt and semantic tokens from the initial image, yielding higher alignment scores than editing-based methods.
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Effective Prompt Pool Learning for Continual Category Discovery
PromptCCD uses Gaussian Mixture Prompts for global class prototypes and PromptCCD++ adds part-level prompt pools for finer representations in continual category discovery from unlabeled streams.
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Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models
Refinement via Regeneration (RvR) reformulates image refinement in unified multimodal models as conditional regeneration using prompt and semantic tokens from the initial image, yielding higher alignment scores than editing-based methods.