7 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…
Multi-view Pyramid Transformer: Look Coarser to See Broader
Gyeongjin Kang, Seungkwon Yang, Seungtae Nam +3
We propose Multi-view Pyramid Transformer (MVP), a scalable multi-view transformer architecture that directly reconstructs large 3D scenes from tens to hundreds of images in a sing…
Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending
Junseok Ko, Jungwoo Kim, Jong-Seok Lee
Concept erasure has emerged as a key research direction for ensuring safe and ethical image synthesis in Text-to-Image (T2I) models. While existing studies have explored concept er…
Coarse-to-Fine: Progressive Image Compression for Semantically Hierarchical Classification
Jungwoo Kim, Jun-Hyuk Kim, Jong-Seok Lee
Recent advances in learned image compression (LIC) have enabled practical deployments, spurring active research into image compression for machines and progressive coding schemes.…
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.…
Progressive Learned Image Compression for Machine Perception
Jungwoo Kim, Jun-Hyuk Kim, Jong-Seok Lee
Recent advances in learned image codecs have extended from human perception toward machine perception However, progressive image compression with fine granular scalability (FGS)-wh…