Kyungryeol Lee — accepted AI-conference papers

2026

Training-free Mixed-Resolution Latent Upsampling for Spatially Accelerated Diffusion Transformers

Wongi Jeong, Kyungryeol Lee, Hoigi Seo, Se Young Chun

CVPR 2026

Diffusion transformers (DiTs) offer excellent scalability for high-fidelity generation, but their computational overhead poses a great challenge for practical deployment. Existing acceleration methods primarily exploit the temporal dimension, whereas spatial acceleration remains underexplored. In th

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2025

Efficient Personalization of Quantized Diffusion Model without Backpropagation

Hoigi Seo, Wongi Jeong, Kyungryeol Lee, Se Young Chun

CVPR 2025poster

Diffusion models have shown remarkable performance in image synthesis, but they demand extensive computational and memory resources for training, fine-tuning and inference. Although advanced quantization techniques have successfully minimized memory usage for inference, training and fine-tuning thes…

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