2 citations · 3 across the 17 of their papers we have counts for
20 papers
DiscoDemo: Discovering Efficient and Diverse Robot Demonstrations for Imitation Learning
Minho Park, Kinam Kim, Donghu Kim +6
Behavior cloning for robotic manipulation is highly sensitive to the coverage of its training data, yet collecting diverse successful demonstrations remains costly. We study reinfo…
An Agentic Framework for Proactive Robots with Procedural Assistance Memory
Dohyun Lee, Minho Park, Jeonghoon Park +5
Proactive robots should anticipate user needs and provide assistance before being explicitly asked. A straightforward approach is to infer human intentions from commonsense knowled…
ReDesign: Recovering Editable Design Structures from Images via Agentic Decomposition
Jooyeol Yun, Jintae Park, Hyesu Lim +3
Recovering an editable design file from a raster image is a common and costly bottleneck in modern design workflows, yet remains challenging since editability depends on recovering…
Probability-Conserving Flow Guidance
Parsa Esmati, Junha Hyung, Amirhossein Dadashzadeh +2
Diffusion and flow-based generative models dominate visual synthesis, with guidance aligning samples to user input and improving perceptual quality. However, Classifier-Free Guidan…
Not the Example, but the Process: How Self-Generated Examples Enhance LLM Reasoning
Daehoon Gwak, Minseo Jung, Junwoo Park +4
Recent studies have shown that Large Language Models (LLMs) can improve their reasoning performance through self-generated few-shot examples, achieving results comparable to manual…
Infinite-Homography as Robust Conditioning for Camera-Controlled Video Generation
Min-Jung Kim, Jeongho Kim, Hoiyeong Jin +2
Recent progress in video diffusion models has spurred growing interest in camera-controlled novel-view video generation for dynamic scenes, aiming to provide creators with cinemati…
EgoX: Egocentric Video Generation from a Single Exocentric Video
Taewoong Kang, Kinam Kim, Dohyeon Kim +3
Egocentric perception enables humans to experience and understand the world directly from their own point of view. Translating exocentric (third-person) videos into egocentric (fir…
InsertAnywhere: Geometrically Grounded and Optics-Aware Video Object Insertion
Hoiyeong Jin, Hyojin Jang, Junha Hyung +6
Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) remains challenging due to inadequate 4D s…
ACG: Action Coherence Guidance for Flow-based Vision-Language-Action models
Minho Park, Kinam Kim, Junha Hyung +5
Diffusion and flow matching models have emerged as powerful robot policies, enabling Vision-Language-Action (VLA) models to generalize across diverse scenes and instructions. Yet,…
Reward-Weighted Sampling: Enhancing Non-Autoregressive Characteristics in Masked Diffusion LLMs
Daehoon Gwak, Minseo Jung, Junwoo Park +4
Masked diffusion models (MDMs) offer a promising non-autoregressive alternative for large language modeling. Standard decoding methods for MDMs, such as confidence-based sampling,…
Temporal In-Context Fine-Tuning with Temporal Reasoning for Versatile Control of Video Diffusion Models
Kinam Kim, Junha Hyung, Jaegul Choo
Recent advances in text-to-video diffusion models have enabled high-quality video synthesis, but controllable generation remains challenging, particularly under limited data and co…
Spatiotemporal Skip Guidance for Enhanced Video Diffusion Sampling
Junha Hyung, Kinam Kim, Susung Hong +2
Diffusion models have emerged as a powerful tool for generating high-quality images, videos, and 3D content. While sampling guidance techniques like CFG improve quality, they reduc…
SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars
Jaeseong Lee, Taewoong Kang, Marcel C. Bühler +5
Recent advancements in head avatar rendering using Gaussian primitives have achieved significantly high-fidelity results. Although precise head geometry is crucial for applications…
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
Junha Hyung, Susung Hong, Sungwon Hwang +3
3D reconstruction from multi-view images is one of the fundamental challenges in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a promising tec…
SelfSwapper: Self-Supervised Face Swapping via Shape Agnostic Masked AutoEncoder
Jaeseong Lee, Junha Hyung, Sohyun Jeong +1
Face swapping has gained significant attention for its varied applications. Most previous face swapping approaches have relied on the seesaw game training scheme, also known as the…
Text2Control3D: Controllable 3D Avatar Generation in Neural Radiance Fields using Geometry-Guided Text-to-Image Diffusion Model
Sungwon Hwang, Junha Hyung, Jaegul Choo
Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question…
MagiCapture: High-Resolution Multi-Concept Portrait Customization
Junha Hyung, Jaeyo Shin, Jaegul Choo
Large-scale text-to-image models including Stable Diffusion are capable of generating high-fidelity photorealistic portrait images. There is an active research area dedicated to pe…
FaceCLIPNeRF: Text-driven 3D Face Manipulation using Deformable Neural Radiance Fields
Sungwon Hwang, Junha Hyung, Daejin Kim +2
As recent advances in Neural Radiance Fields (NeRF) have enabled high-fidelity 3D face reconstruction and novel view synthesis, its manipulation also became an essential task in 3D…
PixelHuman: Animatable Neural Radiance Fields from Few Images
Gyumin Shim, Jaeseong Lee, Junha Hyung +1
In this paper, we propose PixelHuman, a novel human rendering model that generates animatable human scenes from a few images of a person with unseen identity, views, and poses. Pre…
Local 3D Editing via 3D Distillation of CLIP Knowledge
Junha Hyung, Sungwon Hwang, Daejin Kim +2
3D content manipulation is an important computer vision task with many real-world applications (e.g., product design, cartoon generation, and 3D Avatar editing). Recently proposed…