5 papers
Rectifying Mask via Entropy for Distractor-Free 3DGS in Ambiguous Scenarios
Wongi Park, Jiyeon Lim, Minjae Lee +6
We present RefineSplat, a systematic framework that effectively constructs transient masks to identify diverse ambiguous distractors. To do this, we qualitatively and quantitativel…
Difix3D-W: Distractor-Free Few-Shot 3D Gaussian Splatting in the Wild
Wongi Park, Jordan A. James, Myeongseok Nam +4
We propose Difix3D-W, a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors, occlusion, and appearance variation. Unlike existi…
ForestSplats: Deformable transient field for Gaussian Splatting in the Wild
Wongi Park, Myeongseok Nam, Siwon Kim +2
Recently, 3D Gaussian Splatting (3D-GS) has emerged, showing real-time rendering speeds and high-quality results in static scenes. Although 3D-GS shows effectiveness in static scen…
Veta-GS: View-dependent deformable 3D Gaussian Splatting for thermal infrared Novel-view Synthesis
Myeongseok Nam, Wongi Park, Minsol Kim +2
Recently, 3D Gaussian Splatting (3D-GS) based on Thermal Infrared (TIR) imaging has gained attention in novel-view synthesis, showing real-time rendering. However, novel-view synth…
Efficient Deep Learning Approaches for Processing Ultra-Widefield Retinal Imaging
Siwon Kim, Wooyung Yun, Jeongbin Oh +1
Deep learning has emerged as the predominant solution for classifying medical images. We intend to apply these developments to the ultra-widefield (UWF) retinal imaging dataset. Si…