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Daeyun Shin


My research interests are in artificial intelligence at the intersection of computer vision and computer graphics. I am interested in 3D scene understanding and unsupervised learning. I am advised by Charless Fowlkes.

Education

Since 2017, Ph.D. in Computer Science, University of California, Irvine (advisor: Charless Fowlkes)

2017, M.S. in Computer Science, University of Illinois at Urbana-Champaign (advisor: Derek Hoiem)

2015, B.S. in Computer Science, University of Illinois at Urbana-Champaign

Publications

3D Scene Reconstruction with Multi-layer Depth and Epipolar Transformers
Daeyun Shin, Zhile Ren, Erik Sudderth, Charless Fowlkes
to appear, ICCV, 2019   [pdf]   [poster]   [project website]

Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction
Daeyun Shin, Charless Fowlkes, Derek Hoiem
In CVPR, 2018   [pdf]   [supplementary material]   [poster]   [code]   [project website]

Geometric Pose Affordance: 3D Human Pose with Scene Constraints
Zhe Wang, Liyan Chen, Shaurya Rathore, Daeyun Shin, Charless Fowlkes
In arXiv:1905.07718, 2019   [pdf]

3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera
Tanmay Gupta, Daeyun Shin, Naren Sivagnanadasan, Derek Hoiem
In arXiv:1606.05002, 2016   [arxiv]   [video results]

Completing 3D Object Shape from One Depth Image
Jason Rock, Tanmay Gupta, Justin Thorsen, Junyoung Gwak, Daeyun Shin, Derek Hoiem
In CVPR, 2015   [pdf]   [project website]

Current topics

  • Multi-view 3D volume learning and reconstruction.
  • Learning novel objects.
  • Multi-task learning.
  • Geometry and scene understanding.
  • Adaptive computation