84 citations · 113 across the 13 of their papers we have counts for
13 papers
EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting
Inhwan Bae, Jean Oh, Hae-Gon Jeon
Capturing high-dimensional social interactions and feasible futures is essential for predicting trajectories. To address this complex nature, several attempts have been devoted to…
High-fidelity 3D Human Digitization from Single 2K Resolution Images
Sang-Hun Han, Min-Gyu Park, Ju Hong Yoon +3
High-quality 3D human body reconstruction requires high-fidelity and large-scale training data and appropriate network design that effectively exploits the high-resolution input im…
Scene Structure Guidance Network: Unfolding Graph Partitioning into Pixel-Wise Feature Learning
Jisu Shin, Seunghyun Shin, Hae-Gon Jeon
Understanding the informative structures of scenes is essential for low-level vision tasks. Unfortunately, it is difficult to obtain a concrete visual definition of the informative…
Self-Supervised 3D Traversability Estimation with Proxy Bank Guidance
Jihwan Bae, Junwon Seo, Taekyung Kim +3
Traversability estimation for mobile robots in off-road environments requires more than conventional semantic segmentation used in constrained environments like on-road conditions.…
Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction
Inhwan Bae, Jin-Hwi Park, Hae-Gon Jeon
Modeling the dynamics of people walking is a problem of long-standing interest in computer vision. Many previous works involving pedestrian trajectory prediction define a particula…
Learning Depth from Focus in the Wild
Changyeon Won, Hae-Gon Jeon
For better photography, most recent commercial cameras including smartphones have either adopted large-aperture lens to collect more light or used a burst mode to take multiple ima…
AI-based automated Meibomian gland segmentation, classification and reflection correction in infrared Meibography
Ripon Kumar Saha, A. M. Mahmud Chowdhury, Kyung-Sun Na +6
Purpose: Develop a deep learning-based automated method to segment meibomian glands (MG) and eyelids, quantitatively analyze the MG area and MG ratio, estimate the meiboscore, and…
Non-Probability Sampling Network for Stochastic Human Trajectory Prediction
Inhwan Bae, Jin-Hwi Park, Hae-Gon Jeon
Capturing multimodal natures is essential for stochastic pedestrian trajectory prediction, to infer a finite set of future trajectories. The inferred trajectories are based on obse…
Facial Depth and Normal Estimation using Single Dual-Pixel Camera
Minjun Kang, Jaesung Choe, Hyowon Ha +4
Many mobile manufacturers recently have adopted Dual-Pixel (DP) sensors in their flagship models for faster auto-focus and aesthetic image captures. Despite their advantages, resea…
Explainable Semantic Mapping for First Responders
Jean Oh, Martial Hebert, Hae-Gon Jeon +3
One of the key challenges in the semantic mapping problem in postdisaster environments is how to analyze a large amount of data efficiently with minimal supervision. To address thi…
DPSNet: End-to-end Deep Plane Sweep Stereo
Sunghoon Im, Hae-Gon Jeon, Stephen Lin +1
Multiview stereo aims to reconstruct scene depth from images acquired by a camera under arbitrary motion. Recent methods address this problem through deep learning, which can utili…
EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth from Light Field Images
Changha Shin, Hae-Gon Jeon, Youngjin Yoon +2
Light field cameras capture both the spatial and the angular properties of light rays in space. Due to its property, one can compute the depth from light fields in uncontrolled lig…
Robust Depth Estimation from Auto Bracketed Images
Sunghoon Im, Hae-Gon Jeon, In So Kweon
As demand for advanced photographic applications on hand-held devices grows, these electronics require the capture of high quality depth. However, under low-light conditions, most…