3 citations · 4 across the 10 of their papers we have counts for
11 papers
Revisiting Numerical Forecasting Models for Language-Based Trajectory Prediction
JunGyu Lee, Inhwan Bae, Hae-Gon Jeon
Language-based trajectory predictors represent coordinates as discrete tokens and learn auxiliary tasks such as destination and group reasoning. This formulation enables the model…
ComPose: When to Trust Hands for Object Pose Tracking
Jisu Shin, Junoh Lee, JunGyu Lee +5
Reconstructing the motion of objects from videos is a key component for embodied AI and robot manipulation. While diverse approaches to object pose tracking have been studied, they…
Relaxed Rigidity with Ray-based Grouping for Dynamic Gaussian Splatting
Junoh Lee, Junmyeong Lee, Yeon-Ji Song +4
The reconstruction of dynamic 3D scenes using 3D Gaussian Splatting has shown significant promise. A key challenge, however, remains in modeling realistic motion, as most methods f…
Continuous Locomotive Crowd Behavior Generation
Inhwan Bae, Junoh Lee, Hae-Gon Jeon
Modeling and reproducing crowd behaviors are important in various domains including psychology, robotics, transport engineering and virtual environments. Conventional methods have…
Fully Explicit Dynamic Gaussian Splatting
Junoh Lee, Chang-Yeon Won, Hyunjun Jung +2
3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of t…
Kinetic Typography Diffusion Model
Seonmi Park, Inhwan Bae, Seunghyun Shin +1
This paper introduces a method for realistic kinetic typography that generates user-preferred animatable 'text content'. We draw on recent advances in guided video diffusion models…
SingularTrajectory: Universal Trajectory Predictor Using Diffusion Model
Inhwan Bae, Young-Jae Park, Hae-Gon Jeon
There are five types of trajectory prediction tasks: deterministic, stochastic, domain adaptation, momentary observation, and few-shot. These associated tasks are defined by variou…
Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
Inhwan Bae, Junoh Lee, Hae-Gon Jeon
Language models have demonstrated impressive ability in context understanding and generative performance. Inspired by the recent success of language foundation models, in this pape…
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…
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…
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…