2 citations · 5 across the 25 of their papers we have counts for
6 papers · 1 filter
SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis
Hyojun Go, Byeongjun Park, Jiho Jang +3
Text-based generation and editing of 3D scenes hold significant potential for streamlining content creation through intuitive user interactions. While recent advances leverage 3D G…
TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models
Hyeongmin Lee, Jin-Young Kim, Kyungjune Baek +18
In this work, we discuss evaluating video foundation models in a fair and robust manner. Unlike language or image foundation models, many video foundation models are evaluated with…
Diffusion Model Patching via Mixture-of-Prompts
Seokil Ham, Sangmin Woo, Jin-Young Kim +3
We present Diffusion Model Patching (DMP), a simple method to boost the performance of pre-trained diffusion models that have already reached convergence, with a negligible increas…
Pegasus-v1 Technical Report
Raehyuk Jung, Hyojun Go, Jaehyuk Yi +41
This technical report introduces Pegasus-1, a multimodal language model specialized in video content understanding and interaction through natural language. Pegasus-1 is designed t…
Denoising Task Difficulty-based Curriculum for Training Diffusion Models
Jin-Young Kim, Hyojun Go, Soonwoo Kwon +1
Diffusion-based generative models have emerged as powerful tools in the realm of generative modeling. Despite extensive research on denoising across various timesteps and noise lev…
Switch Diffusion Transformer: Synergizing Denoising Tasks with Sparse Mixture-of-Experts
Byeongjun Park, Hyojun Go, Jin-Young Kim +3
Diffusion models have achieved remarkable success across a range of generative tasks. Recent efforts to enhance diffusion model architectures have reimagined them as a form of mult…