Search Results for author: Eunsu Kang

Found 8 papers, 2 papers with code

Learned Interpolation for 3D Generation

no code implementations8 Dec 2019 Austin Dill, Songwei Ge, Eunsu Kang, Chun-Liang Li, Barnabas Poczos

The typical approach for incorporating this creative process is to interpolate in a learned latent space so as to avoid the problem of generating unrealistic instances by exploiting the model's learned structure.

3D Generation

Getting Topology and Point Cloud Generation to Mesh

no code implementations8 Dec 2019 Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang

In this work, we explore the idea that effective generative models for point clouds under the autoencoding framework must acknowledge the relationship between a continuous surface, a discretized mesh, and a set of points sampled from the surface.

Point Cloud Generation

LucidDream: Controlled Temporally-Consistent DeepDream on Videos

no code implementations27 Nov 2019 Joel Ruben Antony Moniz, Eunsu Kang, Barnabás Póczos

In this work, we aim to propose a set of techniques to improve the controllability and aesthetic appeal when DeepDream, which uses a pre-trained neural network to modify images by hallucinating objects into them, is applied to videos.

Developing Creative AI to Generate Sculptural Objects

no code implementations20 Aug 2019 Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, Manzil Zaheer, Barnabas Poczos

We explore the intersection of human and machine creativity by generating sculptural objects through machine learning.

Clustering Generating 3D Point Clouds

The Myths of Our Time: Fake News

1 code implementation5 Aug 2019 Vít Růžička, Eunsu Kang, David Gordon, Ankita Patel, Jacqui Fashimpaur, Manzil Zaheer

While the purpose of most fake news is misinformation and political propaganda, our team sees it as a new type of myth that is created by people in the age of internet identities and artificial intelligence.

BIG-bench Machine Learning Misinformation +1

Machinic Surrogates: Human-Machine Relationships in Computational Creativity

no code implementations3 Aug 2019 Ardavan Bidgoli, Eunsu Kang, Daniel Cardoso Llach

This paper uses examples from art and design to argue that this frame is incomplete as it fails to acknowledge the socio-technical nature of AI systems, and the different human agencies involved in their design, implementation, and operation.

BIG-bench Machine Learning

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