4 citations · 7 across the 7 of their papers we have counts for
7 papers
Convex Hull-based Algebraic Constraint for Visual Quadric SLAM
Xiaolong Yu, Junqiao Zhao, Shuangfu Song +4
Using Quadrics as the object representation has the benefits of both generality and closed-form projection derivation between image and world spaces. Although numerous constraints…
LOG-LIO2: A LiDAR-Inertial Odometry with Efficient Uncertainty Analysis
Kai Huang, Junqiao Zhao, Jiaye Lin +4
Uncertainty in LiDAR measurements, stemming from factors such as range sensing, is crucial for LIO (LiDAR-Inertial Odometry) systems as it affects the accurate weighting in the los…
N-Mapping: Normal Guided Neural Non-Projective Signed Distance Fields for Large-scale 3D Mapping
Shuangfu Song, Junqiao Zhao, Kai Huang +3
Accurate and dense mapping in large-scale environments is essential for various robot applications. Recently, implicit neural signed distance fields (SDFs) have shown promising adv…
Multistep feature aggregation framework for salient object detection
Xiaogang Liu Shuang Song
Recent works on salient object detection have made use of multi-scale features in a way such that high-level features and low-level features can collaborate in locating salient obj…
Scale Estimation with Dual Quadrics for Monocular Object SLAM
Shuangfu Song, Junqiao Zhao, Tiantian Feng +2
The scale ambiguity problem is inherently unsolvable to monocular SLAM without the metric baseline between moving cameras. In this paper, we present a novel scale estimation approa…
ViF-SD2E: A Robust Weakly-Supervised Method for Neural Decoding
Jingyi Feng, Yong Luo, Shuang Song
Neural decoding plays a vital role in the interaction between the brain and the outside world. In this paper, we directly decode the movement track of a finger based on the neural…
Unsupervised Joint Learning of Depth, Optical Flow, Ego-motion from Video
Jianfeng Li, Junqiao Zhao, Shuangfu Song +1
Estimating geometric elements such as depth, camera motion, and optical flow from images is an important part of the robot's visual perception. We use a joint self-supervised metho…