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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CV2026

Articulated Object Reconstruction from Rest-State Observation

Daeun Lee, Jaeah Lee, Woosung Kim +2

The paper presents a method to recover both the 3D shape and the joint structure of articulated objects from a single static pose by fusing mesh modeling, vision‑language cues, and…

cs.CV2026

TRiGS: Temporal Rigid-Body Motion for Scalable 4D Gaussian Splatting

Suwoong Yeom, Joonsik Nam, Seunggyu Choi +7

Recent 4D Gaussian Splatting (4DGS) methods achieve impressive dynamic scene reconstruction but often rely on piecewise linear velocity approximations and short temporal windows. T…

cs.CV2026

Extend3D: Town-Scale 3D Generation

Seungwoo Yoon, Jinmo Kim, Jaesik Park

In this paper, we propose Extend3D, a training-free pipeline for 3D scene generation from a single image, built upon an object-centric 3D generative model. To overcome the limitati…

cs.CV2026

Targetless LiDAR-Camera Calibration with Neural Gaussian Splatting

Haebeom Jung, Namtae Kim, Jungwoo Kim +1

Accurate LiDAR-camera calibration is crucial for multi-sensor systems. However, traditional methods often rely on physical targets, which are impractical for real-world deployment.…

cs.CV2025

Metropolis-Hastings Sampling for 3D Gaussian Reconstruction

Hyunjin Kim, Haebeom Jung, Jaesik Park

We propose an adaptive sampling framework for 3D Gaussian Splatting (3DGS) that leverages comprehensive multi-view photometric error signals within a unified Metropolis-Hastings ap…