Daeyun Shin
Cited by
Cited by
Completing 3D Object Shape from One Depth Image
J Rock, T Gupta, J Thorsen, JY Gwak, D Shin, D Hoiem
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction
D Shin, CC Fowlkes, D Hoiem
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
3D Scene Reconstruction with Multi-layer Depth and Epipolar Transformers
D Shin, Z Ren, EB Sudderth, CC Fowlkes
Proceedings of the IEEE International Conference on Computer Vision, 2172-2182, 2019
Geometric Pose Affordance: 3D Human Pose with Scene Constraints
Z Wang, L Chen, S Rathore, D Shin, C Fowlkes
arXiv preprint arXiv:1905.07718, 2019
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation
Z Wang, D Shin, CC Fowlkes
ECCV 2020 Workshops, 523-540, 2020
Domain decluttering: Simplifying images to mitigate synthetic-real domain shift and improve depth estimation
Y Zhao, S Kong, D Shin, C Fowlkes
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Modular framework for visuomotor language grounding
K Nottingham, L Liang, D Shin, CC Fowlkes, R Fox, S Singh
arXiv preprint arXiv:2109.02161, 2021
3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera
T Gupta, D Shin, N Sivagnanadasan, D Hoiem
arXiv preprint arXiv:1606.05002, 2016
Learning viewer-centered projections for 3D shape completion
D Shin
University of Illinois at Urbana-Champaign, 2017
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