most citedTowards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models

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

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cs.CV2024

Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion

Sanghyun Kim, Seohyeon Jung, Balhae Kim +3

This paper addresses the societal concerns arising from large-scale text-to-image diffusion models for generating potentially harmful or copyrighted content. Existing models rely h…

cs.CV2023

Slot-Mixup with Subsampling: A Simple Regularization for WSI Classification

Seongho Keum, Sanghyun Kim, Soojeong Lee +1

Whole slide image (WSI) classification requires repetitive zoom-in and out for pathologists, as only small portions of the slide may be relevant to detecting cancer. Due to the lac…

cs.CV2023★ 5 cited

Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models

Sanghyun Kim, Seohyeon Jung, Balhae Kim +3

Large-scale image generation models, with impressive quality made possible by the vast amount of data available on the Internet, raise social concerns that these models may generat…

cs.CV2023★ 4 cited

Relational Context Learning for Human-Object Interaction Detection

Sanghyun Kim, Deunsol Jung, Minsu Cho

Recent state-of-the-art methods for HOI detection typically build on transformer architectures with two decoder branches, one for human-object pair detection and the other for inte…

cs.CV2023★ 2 cited

Devil's on the Edges: Selective Quad Attention for Scene Graph Generation

Deunsol Jung, Sanghyun Kim, Won Hwa Kim +1

Scene graph generation aims to construct a semantic graph structure from an image such that its nodes and edges respectively represent objects and their relationships. One of the m…