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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
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Blog Post number 1
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portfolio
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publications
DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model
Published in arXiv, 2023
Reconstructing diverse 3D objects from text or a single image with 2D diffusion priors.
Authors: Hoigi Seo*, Hayeon Kim, Gwanghyun Kim and Se Young Chun. (* co-first author)
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BeyondScene: Higher-Resolution Human-Centric Scene Generation With Pretrained Diffusion
Published in European Conference on Computer Vision (ECCV), 2024
Generating detailed, human-centric scenes beyond 8K with pretrained diffusion models.
Authors: Gwanghyun Kim*, Hayeon Kim*, Hoigi Seo*, Dong Un Kang* and Se Young Chun. (* co-first author)
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INTRA: Interaction Relationship-aware Weakly Supervised Affordance Grounding
Published in European Conference on Computer Vision (ECCV), Twelfth International Workshop on Assistive Computer Vision and Robotics (ACVR24) (oral), 2024
Learning interaction-aware affordance grounding from weak supervision.
Authors: Ji Ha Jang*, Hoigi Seo* and Se Young Chun. (* co-first author)
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Harmonization for a black-box deep learning model
Published in International Society for Magnetic Resonance in Medicine (ISMRM) (oral, Summa cum laude), 2025
Harmonizing MR images for black-box models without access to model parameters.
Authors: Minjun Kim, Hwihun Jeong, Hoigi Seo, Se Young Chun and Jongho Lee
Efficient Personalization of Quantized Diffusion Model without Backpropagation
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), The 2nd Workshop on Efficient and On-Device Generation (EDGE), 2025
Personalizing quantized diffusion models without backpropagation.
Authors: Hoigi Seo*, Wongi Jeong*, Kyungryeol Lee and Se Young Chun. (* co-first author)
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On Geometrical Properties of Text Token Embeddings for Strong Semantic Binding in Text-to-Image Generation
Published in arXiv, 2025
Using text embedding geometry to improve semantic binding in text-to-image generation.
Authors: Hoigi Seo*, Junseo Bang*, Haechang Lee*, Joohoon Lee, Byung Hyun Lee and Se Young Chun. (* co-first author)
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Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation
Published in International Conference on Machine Learning (ICML), 2025
Skipping and reusing text encoder layers for memory-efficient text-to-image generation.
Authors: Hoigi Seo*, Wongi Jeong*, Jae-sun Seo and Se Young Chun. (* co-first author)
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On Epistemic Uncertainty of Visual Tokens for Object Hallucinations in Large Vision-Language Models
Published in Neural Information Processing Systems (NeurIPS), 2025
Identifying and masking uncertain visual tokens to reduce object hallucinations without training.
Authors: Hoigi Seo*, Dong Un Kang*, Hyunjin Cho, Joohoon Lee and Se Young Chun. (* co-first author)
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Erasing Thousands of Concepts: Towards Scalable and Practical Concept Erasure for Text-to-Image Diffusion Model
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (Compute Transparency Champion Award), 2026
Scalable concept erasure that removes thousands of concepts while preserving generation quality.
Authors: Hoigi Seo*, Byung Hyun Lee*, Jaehyun Cho, Sungjin Lim and Se Young Chun. (* co-first author)
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Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
Training-free, low-resolution previews that stay perceptually consistent with high-resolution outputs.
Authors: Hoigi Seo*, Wongi Jeong* and Se Young Chun. (* co-first author)
Training-free Mixed-Resolution Latent Upsampling for Spatially Accelerated Diffusion Transformers
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (Highlight · Top 3.4%), 2026
Region-adaptive latent upsampling accelerates diffusion transformers with minimal quality degradation.
Authors: Wongi Jeong*, Kyeongryeol Lee*, Hoigi Seo and Se Young Chun. (* co-first author)
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Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
Published in International Conference on Machine Learning (ICML), 2026
Coordinating guidance and stochasticity schedules for diffusion-based inverse problems.
Authors: Junseo Bang*, Dongju Moon*, Hoigi Seo, Seongmin Hong and Se Young Chun. (* co-first author)
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Strong Helps Weak: Directional Cross-Modal Alignment Transfer in Multi-modal LLMs
Published in Neural Information Processing Systems (NeurIPS) (Spotlight · Top 1.3%), 2026
Transferring alignment from strong vision models to audio and video MLLMs without further fine-tuning.
Authors: Hoigi Seo*, Byung Hyun Lee*, Minjun Kim*, Dohyun Mah, Jongho Lee and Se Young Chun. (* co-first author)
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Recovering Diversity in Distilled Diffusion Models via Low-Rank Policy-Optimized Merging
Published in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2026
Recovering diversity in few-step diffusion models through low-rank, policy-optimized teacher-student merging.
Authors: Hoigi Seo, Woojae Han, Joohoon Lee and Se Young Chun.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
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