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cs.CV2026

HOPE: Hand-Object Pressure Estimation from Monocular Videos

Subin Jeon, Byungjun Kim, Hanbyul Joo

Estimating physical pressure from vision is essential for understanding contact-rich hand-object interaction. However, prior vision-based pressure estimation methods are largely li…

cs.CV2026

Scenes as Objects, Not Primitives: Instance-Structured 3D Tokenization from Unposed Views

Mijin Yoo, In Cho, Subin Jeon +3

A 3D scene is understood through its objects, not the primitives that compose them. Yet feed-forward reconstruction methods output dense, unstructured sets of points or Gaussians,…

cs.CV2025

ExploreGS: Explorable 3D Scene Reconstruction with Virtual Camera Samplings and Diffusion Priors

Minsu Kim, Subin Jeon, In Cho +2

Recent advances in novel view synthesis (NVS) have enabled real-time rendering with 3D Gaussian Splatting (3DGS). However, existing methods struggle with artifacts and missing regi…

cs.CV2025

Unsupervised Monocular 3D Keypoint Discovery from Multi-View Diffusion Priors

Subin Jeon, In Cho, Junyoung Hong +2

Most existing 3D keypoint estimation methods rely on manual annotations or calibrated multi-view images, both of which are expensive to collect. This paper introduces KeyDiff3D, a…

cs.CV2025

Representing 3D Shapes With 64 Latent Vectors for 3D Diffusion Models

In Cho, Youngbeom Yoo, Subin Jeon +1

Constructing a compressed latent space through a variational autoencoder (VAE) is the key for efficient 3D diffusion models. This paper introduces COD-VAE that encodes 3D shapes in…

cs.CV2024

Hierarchically Structured Neural Bones for Reconstructing Animatable Objects from Casual Videos

Subin Jeon, In Cho, Minsu Kim +2

We propose a new framework for creating and easily manipulating 3D models of arbitrary objects using casually captured videos. Our core ingredient is a novel hierarchy deformation…