Jan 29, 2011, I gave a public speech to PersonaTech. This is the document originally hosted on iwork.com, but since Apple shutdown iwork.com, I hope slideshare.net can help this presentation find a place to stay.
論文紹介:「Amodal Completion via Progressive Mixed Context Diffusion」「Amodal Insta...Toru Tamaki
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Katherine Xu, Lingzhi Zhang, Jianbo Shi; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, "Amodal Completion via Progressive Mixed Context Diffusion"CVPR2024
https://openaccess.thecvf.com/content/CVPR2024/html/Xu_Amodal_Completion_via_Progressive_Mixed_Context_Diffusion_CVPR_2024_paper.html
Minh Tran, Khoa Vo, Tri Nguyen, and Ngan Le,"Amodal Instance Segmentation with Diffusion Shape Prior Estimation"ACCV 2024
https://uark-aicv.github.io/AISDiff/
This study aims to develop an interactive idea-generation support system that enables users to consider the potential side effects of realizing new ideas.
In idea generation, confirmation bias often leads to an excessive focus on ``convenience,'' which can result in the oversight of unintended consequences, referred to as the ``side effects of convenience.''
To address this, we explored methods to alleviate user biases and expand perspectives through system-supported dialogue, facilitating a broader consideration of potential side effects.
The proposed system employs a stepwise idea-generation process supported by large language models (LLMs), enabling users to refine their ideas interactively.
By dividing the ideation process into distinct stages, the system mitigates biases at each stage while promoting ideas' concretization and identifying side effects through visually supported dialogues.
Preliminary evaluation suggests that engaging with the proposed system fosters awareness of diverse perspectives on potential side effects and facilitates the generation of ideas that proactively address these issues.