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20172022
most citedWeakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer Labels

29 citations · 129 across the 15 of their papers we have counts for

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cs.CV202217 cited

REGTR: End-to-end Point Cloud Correspondences with Transformers

Zi Jian Yew, Gim Hee Lee

Despite recent success in incorporating learning into point cloud registration, many works focus on learning feature descriptors and continue to rely on nearest-neighbor feature ma…

cs.CV202014 cited

Weakly Supervised Generative Network for Multiple 3D Human Pose Hypotheses

Chen Li, Gim Hee Lee

3D human pose estimation from a single image is an inverse problem due to the inherent ambiguity of the missing depth. Several previous works addressed the inverse problem by gener…

cs.CV20202 cited

Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View Geometry

He Chen, Pengfei Guo, Pengfei Li +2

Epipolar constraints are at the core of feature matching and depth estimation in current multi-person multi-camera 3D human pose estimation methods. Despite the satisfactory perfor…

cs.CV20206 cited

HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization

Jiahao Lin, Gim Hee Lee

Current works on multi-person 3D pose estimation mainly focus on the estimation of the 3D joint locations relative to the root joint and ignore the absolute locations of each pose.…

cs.CV20207 cited

Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation

Meng Tian, Marcelo H Ang, Gim Hee Lee

We present a novel learning approach to recover the 6D poses and sizes of unseen object instances from an RGB-D image. To handle the intra-class shape variation, we propose a deep…

cs.CV2020

Few-shot 3D Point Cloud Semantic Segmentation

Na Zhao, Tat-Seng Chua, Gim Hee Lee

Many existing approaches for 3D point cloud semantic segmentation are fully supervised. These fully supervised approaches heavily rely on large amounts of labeled training data tha…