74 citations · 204 across the 15 of their papers we have counts for
15 papers
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep Thinking
Chang Nie, Yiqing Xu, Guangming Wang +3
Moving object segmentation plays a vital role in understanding dynamic visual environments. While existing methods rely on multi-frame image sequences to identify moving objects, s…
SC-NeRF: Self-Correcting Neural Radiance Field with Sparse Views
Liang Song, Guangming Wang, Jiuming Liu +3
In recent studies, the generalization of neural radiance fields for novel view synthesis task has been widely explored. However, existing methods are limited to objects and indoor…
End-to-end 2D-3D Registration between Image and LiDAR Point Cloud for Vehicle Localization
Guangming Wang, Yu Zheng, Yuxuan Wu +5
Robot localization using a built map is essential for a variety of tasks including accurate navigation and mobile manipulation. A popular approach to robot localization is based on…
RegFormer: An Efficient Projection-Aware Transformer Network for Large-Scale Point Cloud Registration
Jiuming Liu, Guangming Wang, Zhe Liu +3
Although point cloud registration has achieved remarkable advances in object-level and indoor scenes, large-scale registration methods are rarely explored. Challenges mainly arise…
3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion
Chaokang Jiang, Guangming Wang, Yanzi Miao +1
3D scene flow characterizes how the points at the current time flow to the next time in the 3D Euclidean space, which possesses the capacity to infer autonomously the non-rigid mot…
Unsupervised Learning of 3D Scene Flow with 3D Odometry Assistance
Guangming Wang, Zhiheng Feng, Chaokang Jiang +1
Scene flow represents the 3D motion of each point in the scene, which explicitly describes the distance and the direction of each point's movement. Scene flow estimation is used in…