79 citations · 185 across the 18 of their papers we have counts for
11 papers · 1 filter
Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation
Yumi Lee, Harim Oh, Hyoryung Kim +52
The rapid advancement of vision-language models (VLMs) has accelerated progress in computational pathology; however, whole-slide image (WSI)-based pathology report generation remai…
Human Interaction-Aware 3D Reconstruction from a Single Image
Gwanghyun Kim, Junghun James Kim, Suh Yoon Jeon +2
Reconstructing textured 3D human models from a single image is fundamental for AR/VR and digital human applications. However, existing methods mostly focus on single individuals an…
LaMoGen: Laban Movement-Guided Diffusion for Text-to-Motion Generation
Heechang Kim, Gwanghyun Kim, Se Young Chun
Diverse human motion generation is an increasingly important task, having various applications in computer vision, human-computer interaction and animation. While text-to-motion sy…
GeoMan: Temporally Consistent Human Geometry Estimation using Image-to-Video Diffusion
Gwanghyun Kim, Xueting Li, Ye Yuan +5
Estimating accurate and temporally consistent 3D human geometry from videos is a challenging problem in computer vision. Existing methods, primarily optimized for single images, of…
PersonaCraft: Personalized and Controllable Full-Body Multi-Human Scene Generation Using Occlusion-Aware 3D-Conditioned Diffusion
Gwanghyun Kim, Suh Yoon Jeon, Seunggyu Lee +1
We present PersonaCraft, a framework for controllable and occlusion-robust full-body personalized image synthesis of multiple individuals in complex scenes. Current methods struggl…
BeyondScene: Higher-Resolution Human-Centric Scene Generation With Pretrained Diffusion
Gwanghyun Kim, Hayeon Kim, Hoigi Seo +2
Generating higher-resolution human-centric scenes with details and controls remains a challenge for existing text-to-image diffusion models. This challenge stems from limited train…
Detailed Human-Centric Text Description-Driven Large Scene Synthesis
Gwanghyun Kim, Dong Un Kang, Hoigi Seo +2
Text-driven large scene image synthesis has made significant progress with diffusion models, but controlling it is challenging. While using additional spatial controls with corresp…
DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model
Hoigi Seo, Hayeon Kim, Gwanghyun Kim +1
The increasing demand for high-quality 3D content creation has motivated the development of automated methods for creating 3D object models from a single image and/or from a text p…
PODIA-3D: Domain Adaptation of 3D Generative Model Across Large Domain Gap Using Pose-Preserved Text-to-Image Diffusion
Gwanghyun Kim, Ji Ha Jang, Se Young Chun
Recently, significant advancements have been made in 3D generative models, however training these models across diverse domains is challenging and requires an huge amount of traini…
DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model
Gwanghyun Kim, Se Young Chun
Recent 3D generative models have achieved remarkable performance in synthesizing high resolution photorealistic images with view consistency and detailed 3D shapes, but training th…
DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation
Gwanghyun Kim, Taesung Kwon, Jong Chul Ye
Recently, GAN inversion methods combined with Contrastive Language-Image Pretraining (CLIP) enables zero-shot image manipulation guided by text prompts. However, their applications…