collaborators

6 papers

cs.DC2025

Range Asymmetric Numeral Systems-Based Lightweight Intermediate Feature Compression for Split Computing of Deep Neural Networks

Mingyu Sung, Suhwan Im, Vikas Palakonda +1

Split computing distributes deep neural network inference between resource-constrained edge devices and cloud servers but faces significant communication bottlenecks when transmitt…

cs.CV2025

No Pose Estimation? No Problem: Pose-Agnostic and Instance-Aware Test-Time Adaptation for Monocular Depth Estimation

Mingyu Sung, Hyeonmin Choe, Il-Min Kim +2

Monocular depth estimation (MDE), inferring pixel-level depths in single RGB images from a monocular camera, plays a crucial and pivotal role in a variety of AI applications demand…

cs.LG2025

Memory- and Latency-Constrained Inference of Large Language Models via Adaptive Split Computing

Mingyu Sung, Vikas Palakonda, Suhwan Im +4

Large language models (LLMs) have achieved near-human performance across diverse reasoning tasks, yet their deployment on resource-constrained Internet-of-Things (IoT) devices rema…

cs.DC2025

Why Should the Server Do It All?: A Scalable, Versatile, and Model-Agnostic Framework for Server-Light DNN Inference over Massively Distributed Clients via Training-Free Intermediate Feature Compression

Mingyu Sung, Suhwan Im, Daeho Bang +3

Modern DNNs often rely on edge-cloud model partitioning (MP), but widely used schemes fix shallow, static split points that underutilize edge compute and concentrate latency and en…

cs.CV2025

H2-Cache: A Novel Hierarchical Dual-Stage Cache for High-Performance Acceleration of Generative Diffusion Models

Mingyu Sung, Il-Min Kim, Sangseok Yun +1

Diffusion models have emerged as state-of-the-art in image generation, but their practical deployment is hindered by the significant computational cost of their iterative denoising…

cs.CV2025

GLYPH-SR: Can We Achieve Both High-Quality Image Super-Resolution and High-Fidelity Text Recovery via VLM-guided Latent Diffusion Model?

Mingyu Sung, Seungjae Ham, Kangwoo Kim +4

Image super-resolution(SR) is fundamental to many vision system-from surveillance and autonomy to document analysis and retail analytics-because recovering high-frequency details,…