From the 1 of 6 linked papers with an AI index.
8 citations · 8 across the 4 of their papers we have counts for
6 papers
AtlasLC: Fast Codec-Ready Compression of Object-Centric 3D Gaussian Splatting
ByungHyun Kim, Jinwoo Jeon, Woontack Woo
AtlasLC is a source‑free, training‑free pipeline that quickly compresses object‑centric 3D Gaussian Splatting assets for XR, cutting preparation and compression time while preservi…
Universal Time-Series Representation Learning: A Survey
Patara Trirat, Yooju Shin, Junhyeok Kang +6
Time-series data exists in every corner of real-world systems and services, ranging from satellites in the sky to wearable devices on human bodies. Learning representations by extr…
Semantic-Fast-SAM: Efficient Semantic Segmenter
Byunghyun Kim
We propose Semantic-Fast-SAM (SFS), a semantic segmentation framework that combines the Fast Segment Anything model with a semantic labeling pipeline to achieve real-time performan…
Accelerating Diffusion via Hybrid Data-Pipeline Parallelism Based on Conditional Guidance Scheduling
Euisoo Jung, Byunghyun Kim, Hyunjin Kim +2
Diffusion models have achieved remarkable progress in high-fidelity image, video, and audio generation, yet inference remains computationally expensive. Nevertheless, current diffu…
Ultra-Light Test-Time Adaptation for Vision--Language Models
Byunghyun Kim
Vision-Language Models (VLMs) such as CLIP achieve strong zero-shot recognition by comparing image embeddings to text-derived class prototypes. However, under domain shift, they su…
Continuous-Time Linear Positional Embedding for Irregular Time Series Forecasting
Byunghyun Kim, Jae-Gil Lee
Irregularly sampled time series forecasting, characterized by non-uniform intervals, is prevalent in practical applications. However, previous research have been focused on regular…