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20232026
most citedDITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model

6 citations · 7 across the 11 of their papers we have counts for

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cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2023

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…

cs.CV2023★ 6 cited

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…