"TRAN-SCEPTION : de/re-constructing our segmented reality" is a group project realised during DfPI 3-day design workshop “Mapping the Machine” at Bartlett, UCL. It is an early-stage exploration of machine learning techniques used for creative practice. We create maps of machinic space to discover their boundaries and potentially begin navigating these worlds as reflections of our own biases and limitations.

In this demo, we use footages from the movie Inception (one that metaphorically matches the theme of our work), deconstruct the images into colour blocks of different categories of objects and then reconstruct another segmented “reality”. The process is like to dream unconsciously with machinic views. The output is oddly familiar.

Technical details

The #machinelearning project is based on Runway ML pre-trained models of Spade-COCO, DeepLab and DeepPrivacy. The datasets used for training are mainly COCO-Stuff 10k/164k and PASCAL VOC 2012.





這個機器學習項目基於Runway ML預訓練模型Spade-COCO, DeepLab和DeepPrivacy。訓練所用的數據庫主要為COCO-Stuff 10k/164k和PASCAL VOC 2012。


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