The first generative framework that anonymizes event streams by synthesizing non-existent identities in an intermediate image domain while preserving structural integrity for downstream perception.
DreamID: High-Fidelity and Fast diffusion-based Face Swapping via Triplet ID Group Learning
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
HydraPrompt uses an Asymmetric Prompt Adapter with fixed real prompts and adaptive fake prompts plus a Conditional Supervised Contrastive loss to achieve SOTA synthetic image detection on benchmarks.
citing papers explorer
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Generative Anonymization in Event Streams
The first generative framework that anonymizes event streams by synthesizing non-existent identities in an intermediate image domain while preserving structural integrity for downstream perception.
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HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection
HydraPrompt uses an Asymmetric Prompt Adapter with fixed real prompts and adaptive fake prompts plus a Conditional Supervised Contrastive loss to achieve SOTA synthetic image detection on benchmarks.