activity
20192022
most citedFFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

14 citations · 28 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20229 cited

Towards Self-Supervised Category-Level Object Pose and Size Estimation

Yisheng He, Haoqiang Fan, Haibin Huang +2

In this work, we tackle the challenging problem of category-level object pose and size estimation from a single depth image. Although previous fully-supervised works have demonstra…

cs.CV20222 cited

FS6D: Few-Shot 6D Pose Estimation of Novel Objects

Yisheng He, Yao Wang, Haoqiang Fan +2

6D object pose estimation networks are limited in their capability to scale to large numbers of object instances due to the close-set assumption and their reliance on high-fidelity…

cs.CV20213 cited

iShape: A First Step Towards Irregular Shape Instance Segmentation

Lei Yang, Yan Zi Wei, Yisheng HE +4

In this paper, we introduce a brand new dataset to promote the study of instance segmentation for objects with irregular shapes. Our key observation is that though irregularly shap…

cs.CV202114 cited

FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

Yisheng He, Haibin Huang, Haoqiang Fan +2

In this work, we present FFB6D, a Full Flow Bidirectional fusion network designed for 6D pose estimation from a single RGBD image. Our key insight is that appearance information in…

cs.CV2019

PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation

Yisheng He, Wei Sun, Haibin Huang +3

In this work, we present a novel data-driven method for robust 6DoF object pose estimation from a single RGBD image. Unlike previous methods that directly regressing pose parameter…