84 citations · 113 across the 13 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…