1 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning
Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai +6
Controllable generation through Stable Diffusion (SD) fine-tuning aims to improve fidelity, safety, and alignment with human guidance. Existing reinforcement learning from human fe…
Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model
Zhuo Zheng, Stefano Ermon, Dongjun Kim +2
Our understanding of the temporal dynamics of the Earth's surface has been advanced by deep vision models, which often require lots of labeled multi-temporal images for training. H…
SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation
Koichi Saito, Dongjun Kim, Takashi Shibuya +4
Sound content creation, essential for multimedia works such as video games and films, often involves extensive trial-and-error, enabling creators to semantically reflect their arti…
PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao +5
The diffusion model performs remarkable in generating high-dimensional content but is computationally intensive, especially during training. We propose Progressive Growing of Diffu…