1 citations · 1 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
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,…
SoccerNet 2024 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +81
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple t…
Deep Learning for Multi-User MIMO Systems: Joint Design of Pilot, Limited Feedback, and Precoding
Jeonghyeon Jang, Hoon Lee, Il-Min Kim +1
In conventional multi-user multiple-input multiple-output (MU-MIMO) systems with frequency division duplexing (FDD), channel acquisition and precoder optimization processes have be…
Transport Capacity Optimization for Resource Allocation in Tera-IoT Networks
Cheol Jeong, Chang-Jae Chun, Won-Yong Shin +1
We present a new adaptive resource optimization strategy that jointly allocates the subwindow and transmit power in multi-device terahertz (THz) band Internet of Things (Tera-IoT)…