2 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
HarmonyView: Harmonizing Consistency and Diversity in One-Image-to-3D
Sangmin Woo, Byeongjun Park, Hyojun Go +2
Recent progress in single-image 3D generation highlights the importance of multi-view coherency, leveraging 3D priors from large-scale diffusion models pretrained on Internet-scale…
Modality Mixer Exploiting Complementary Information for Multi-modal Action Recognition
Sumin Lee, Sangmin Woo, Muhammad Adi Nugroho +1
Due to the distinctive characteristics of sensors, each modality exhibits unique physical properties. For this reason, in the context of multi-modal action recognition, it is impor…
DiffRef3D: A Diffusion-based Proposal Refinement Framework for 3D Object Detection
Se-Ho Kim, Inyong Koo, Inyoung Lee +2
Denoising diffusion models show remarkable performances in generative tasks, and their potential applications in perception tasks are gaining interest. In this paper, we introduce…
Point-DynRF: Point-based Dynamic Radiance Fields from a Monocular Video
Byeongjun Park, Changick Kim
Dynamic radiance fields have emerged as a promising approach for generating novel views from a monocular video. However, previous methods enforce the geometric consistency to dynam…
Denoising Task Routing for Diffusion Models
Byeongjun Park, Sangmin Woo, Hyojun Go +2
Diffusion models generate highly realistic images by learning a multi-step denoising process, naturally embodying the principles of multi-task learning (MTL). Despite the inherent…