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Kim Jun-Seong

7 accepted papers

2025

Dr. Splat: Directly Referring 3D Gaussian Splatting via Direct Language Embedding Registration

CVPR 2025highlight

We introduce Dr. Splat, a novel approach for open-vocabulary 3D scene understanding leveraging 3D Gaussian Splatting. Unlike existing language-embedded 3DGS methods, which rely on a rendering process, our method directly associates language-aligned CLIP embeddings with 3D Gaussians for holistic 3D s…

Cited by 1SourcePDFScholar
2025

SoundBrush: Sound as a Brush for Visual Scene Editing

AAAI 2025technical

We propose SoundBrush, a model that uses sound as a brush to edit and manipulate visual scenes. We extend the generative capabilities of the Latent Diffusion Model (LDM) to incorporate audio information for editing visual scenes. Inspired by existing image-editing works, we frame this task as a supe…

Cited by 0SourcePDFScholar
2024

Factorized Multi-Resolution HashGrid for Efficient Neural Radiance Fields: Execution on Edge-Devices

RA-L 2024

We introduce Fact-Hash, a novel parameter-encoding method for training on-device neural radiance fields. Neural Radiance Fields (NeRF) have proven pivotal in 3D representations, but their applications are limited due to large computational resources. On-device training can open large application fie

Cited by 2SourceScholar
2024

Learning-based Axial Video Motion Magnification

ECCV 2024poster

"Video motion magnification amplifies invisible small motions to be perceptible, which provides humans with a spatially dense and holistic understanding of small motions in the scene of interest. This is based on the premise that magnifying small motions enhances the legibility of motions. In the re…

2024

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs

ICML 2024poster

The multi-plane representation has been highlighted for its fast training and inference across static and dynamic neural radiance fields. This approach constructs relevant features via projection onto learnable grids and interpolating adjacent vertices. However, it has limitations in capturing low-f…

2022

HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields

ECCV 2022poster

"We propose high dynamic range radiance (HDR) fields, HDR-Plenoxels, that learns a plenoptic function of 3D HDR radiance fields, geometry information, and varying camera settings inherent in 2D low dynamic range (LDR) images. Our voxel-based volume rendering pipeline reconstructs HDR radiance fields…