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Variable-Length Tokenization via Learnable Global Merging for Diffusion Transformers
Dong Hoon Lee, Seunghoon Hong
Latent Diffusion Models (LDMs) have become dominant in visual synthesis, but their quality-compute trade-off is largely constrained by the tokenizer's fixed compression ratio. Vari…
Root-Selecting Fixed-Point Inversion for Rectified Flows via Trajectory Straightness
Semin Kim, Jihwan Yoon, Seunghoon Hong
Finding the initial noise that generates a given data sample, known as inversion, is a key component for downstream applications such as training-free image editing. Existing fixed…
Feature Augmentation based Test-Time Adaptation
Younggeol Cho, Youngrae Kim, Junho Yoon +2
Test-time adaptation (TTA) allows a model to be adapted to an unseen domain without accessing the source data. Due to the nature of practical environments, TTA has a limited amount…
MetaWeather: Few-Shot Weather-Degraded Image Restoration
Youngrae Kim, Younggeol Cho, Thanh-Tung Nguyen +2
Real-world weather conditions are intricate and often occur concurrently. However, most existing restoration approaches are limited in their applicability to specific weather condi…