3 papers
cs.CV2025
How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
Wonkwang Lee, Jongwon Jeong, Taehong Moon +4
Motion synthesis for diverse object categories holds great potential for 3D content creation but remains underexplored due to two key challenges: (1) the lack of comprehensive moti…
cs.LG2025
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Jaehyeon Kim, Taehong Moon, Keon Lee +1
We introduce ResGen, an efficient Residual Vector Quantization (RVQ)-based generative model for high-fidelity generation with fast sampling. RVQ improves data fidelity by increasin…
eess.AS2025
DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors
Keon Lee, Dong Won Kim, Jaehyeon Kim +2
Large-scale latent diffusion models (LDMs) excel in content generation across various modalities, but their reliance on phonemes and durations in text-to-speech (TTS) limits scalab…