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cs.CV2026

MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos

Taeyeon Kim, Youngju Na, Jumin Lee +3

Transferring articulated motion from monocular videos to rigged 3D characters is challenging due to pose ambiguity in 2D observations and morphological differences between source a…

cs.CV2026

VERIA: Verification-Centric Multimodal Instance Augmentation for Long-Tailed 3D Object Detection

Jumin Lee, Siyeong Lee, Namil Kim +1

Long-tail distributions in driving datasets pose a fundamental challenge for 3D perception, as rare classes exhibit substantial intra-class diversity yet available samples cover th…

cs.CV2025

Pose-free 3D Gaussian splatting via shape-ray estimation

Youngju Na, Taeyeon Kim, Jumin Lee +3

While generalizable 3D Gaussian splatting enables efficient, high-quality rendering of unseen scenes, it heavily depends on precise camera poses for accurate geometry. In real-worl…

cs.CV2024

Regularizing Dynamic Radiance Fields with Kinematic Fields

Woobin Im, Geonho Cha, Sebin Lee +4

This paper presents a novel approach for reconstructing dynamic radiance fields from monocular videos. We integrate kinematics with dynamic radiance fields, bridging the gap betwee…

cs.CV2024

Extending Segment Anything Model into Auditory and Temporal Dimensions for Audio-Visual Segmentation

Juhyeong Seon, Woobin Im, Sebin Lee +2

Audio-visual segmentation (AVS) aims to segment sound sources in the video sequence, requiring a pixel-level understanding of audio-visual correspondence. As the Segment Anything M…