41 citations · 69 across the 7 of their papers we have counts for
8 papers
Everybody Tracking Every Body
Daeyun Shin, Yunhan Zhao, Shu Kong +2
We address the problem of 3D body pose estimation of multiple interacting people from their egocentric views with centralized coordination. Each individual wears a camera recording…
Modular Framework for Visuomotor Language Grounding
Kolby Nottingham, Litian Liang, Daeyun Shin +3
Natural language instruction following tasks serve as a valuable test-bed for grounded language and robotics research. However, data collection for these tasks is expensive and end…
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation
Zhe Wang, Daeyun Shin, Charless C. Fowlkes
Monocular estimation of 3d human pose has attracted increased attention with the availability of large ground-truth motion capture datasets. However, the diversity of training data…
Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation
Yunhan Zhao, Shu Kong, Daeyun Shin +1
Leveraging synthetically rendered data offers great potential to improve monocular depth estimation and other geometric estimation tasks, but closing the synthetic-real domain gap…
Geometric Pose Affordance: 3D Human Pose with Scene Constraints
Zhe Wang, Liyan Chen, Shaurya Rathore +2
Full 3D estimation of human pose from a single image remains a challenging task despite many recent advances. In this paper, we explore the hypothesis that strong prior information…
3D Scene Reconstruction with Multi-layer Depth and Epipolar Transformers
Daeyun Shin, Zhile Ren, Erik B. Sudderth +1
We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and…
Pixels, voxels, and views: A study of shape representations for single view 3D object shape prediction
Daeyun Shin, Charless C. Fowlkes, Derek Hoiem
The goal of this paper is to compare surface-based and volumetric 3D object shape representations, as well as viewer-centered and object-centered reference frames for single-view 3…
3DFS: Deformable Dense Depth Fusion and Segmentation for Object Reconstruction from a Handheld Camera
Tanmay Gupta, Daeyun Shin, Naren Sivagnanadasan +1
We propose an approach for 3D reconstruction and segmentation of a single object placed on a flat surface from an input video. Our approach is to perform dense depth map estimation…