3 citations · 8 across the 7 of their papers we have counts for
6 papers · 1 filter
GS-Pose: Generalizable Segmentation-based 6D Object Pose Estimation with 3D Gaussian Splatting
Dingding Cai, Janne Heikkilä, Esa Rahtu
This paper introduces GS-Pose, a unified framework for localizing and estimating the 6D pose of novel objects. GS-Pose begins with a set of posed RGB images of a previously unseen…
MuSHRoom: Multi-Sensor Hybrid Room Dataset for Joint 3D Reconstruction and Novel View Synthesis
Xuqian Ren, Wenjia Wang, Dingding Cai +3
Metaverse technologies demand accurate, real-time, and immersive modeling on consumer-grade hardware for both non-human perception (e.g., drone/robot/autonomous car navigation) and…
MSDA: Monocular Self-supervised Domain Adaptation for 6D Object Pose Estimation
Dingding Cai, Janne Heikkilä, Esa Rahtu
Acquiring labeled 6D poses from real images is an expensive and time-consuming task. Though massive amounts of synthetic RGB images are easy to obtain, the models trained on them s…
SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimation
Dingding Cai, Janne Heikkilä, Esa Rahtu
This paper presents an efficient symmetry-agnostic and correspondence-free framework, referred to as SC6D, for 6D object pose estimation from a single monocular RGB image. SC6D req…
OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimation
Dingding Cai, Janne Heikkilä, Esa Rahtu
This paper proposes a universal framework, called OVE6D, for model-based 6D object pose estimation from a single depth image and a target object mask. Our model is trained using pu…
Convolutional Low-Resolution Fine-Grained Classification
Dingding Cai, Ke Chen, Yanlin Qian +1
Successful fine-grained image classification methods learn subtle details between visually similar (sub-)classes, but the problem becomes significantly more challenging if the deta…