6 citations · 7 across the 11 of their papers we have counts for
13 papers
Strong Helps Weak: Directional Cross-Modal Alignment Transfer in Multi-modal LLMs
Hoigi Seo, Byung Hyun Lee, Minjun Kim +3
Multi-modal large language models (MLLMs) achieve strong modality understanding by pairing a large language model (LLM) with an encoder for a target modality such as vision, video,…
Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
Junseo Bang, Dong Ju Mun, Hoigi Seo +2
Generative posterior sampling using diffusion models has emerged as a dominant paradigm for solving inverse problems in imaging, which usually consists of three main components: da…
Erasing Thousands of Concepts: Towards Scalable and Practical Concept Erasure for Text-to-Image Diffusion Models
Hoigi Seo, Byung Hyun Lee, Jaehyun Cho +2
Large-scale text-to-image (T2I) diffusion models deliver remarkable visual fidelity but pose safety risks due to their capacity to reproduce undesirable content, such as copyrighte…
Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models
Wongi Jeong, Hoigi Seo, Se Young Chun
Image generative models have become indispensable tools to yield exquisite high-resolution (HR) images for everyone, ranging from general users to professional designers. However,…
On Epistemic Uncertainty of Visual Tokens for Object Hallucinations in Large Vision-Language Models
Hoigi Seo, Dong Un Kang, Hyunjin Cho +2
Large vision-language models (LVLMs), which integrate a vision encoder (VE) with a large language model, have achieved remarkable success across various tasks. However, there are s…
Training-free Mixed-Resolution Latent Upsampling for Spatially Accelerated Diffusion Transformers
Wongi Jeong, Kyungryeol Lee, Hoigi Seo +1
Diffusion transformers (DiTs) offer excellent scalability for high-fidelity generation, but their computational overhead poses a great challenge for practical deployment. Existing…
Efficient Personalization of Quantized Diffusion Model without Backpropagation
Hoigi Seo, Wongi Jeong, Kyungryeol Lee +1
Diffusion models have shown remarkable performance in image synthesis, but they demand extensive computational and memory resources for training, fine-tuning and inference. Althoug…
Geometrical Properties of Text Token Embeddings for Strong Semantic Binding in Text-to-Image Generation
Hoigi Seo, Junseo Bang, Haechang Lee +3
Text-to-image (T2I) models often suffer from text-image misalignment in complex scenes involving multiple objects and attributes. Semantic binding has attempted to associate the ge…
Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation
Hoigi Seo, Wongi Jeong, Jae-sun Seo +1
Large-scale text encoders in text-to-image (T2I) diffusion models have demonstrated exceptional performance in generating high-quality images from textual prompts. Unlike denoising…
INTRA: Interaction Relationship-aware Weakly Supervised Affordance Grounding
Ji Ha Jang, Hoigi Seo, Se Young Chun
Affordance denotes the potential interactions inherent in objects. The perception of affordance can enable intelligent agents to navigate and interact with new environments efficie…
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…