most citedPV-RCNN++: Semantical Point-Voxel Feature Interaction for 3D Object Detection

3 citations · 7 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20231 cited

Joint Depth Estimation and Mixture of Rain Removal From a Single Image

Yongzhen Wang, Xuefeng Yan, Yanbiao Niu +3

Rainy weather significantly deteriorates the visibility of scene objects, particularly when images are captured through outdoor camera lenses or windshields. Through careful observ…

cs.CV2023

PointGame: Geometrically and Adaptively Masked Auto-Encoder on Point Clouds

Yun Liu, Xuefeng Yan, Zhilei Chen +3

Self-supervised learning is attracting large attention in point cloud understanding. However, exploring discriminative and transferable features still remains challenging due to th…

cs.CV2022

TogetherNet: Bridging Image Restoration and Object Detection Together via Dynamic Enhancement Learning

Yongzhen Wang, Xuefeng Yan, Kaiwen Zhang +4

Adverse weather conditions such as haze, rain, and snow often impair the quality of captured images, causing detection networks trained on normal images to generalize poorly in the…

cs.CV2022

Contrastive Semantic-Guided Image Smoothing Network

Jie Wang, Yongzhen Wang, Yidan Feng +5

Image smoothing is a fundamental low-level vision task that aims to preserve salient structures of an image while removing insignificant details. Deep learning has been explored in…

cs.CV20223 cited

UTOPIC: Uncertainty-aware Overlap Prediction Network for Partial Point Cloud Registration

Zhilei Chen, Honghua Chen, Lina Gong +5

High-confidence overlap prediction and accurate correspondences are critical for cutting-edge models to align paired point clouds in a partial-to-partial manner. However, there inh…

cs.CV20223 cited

PV-RCNN++: Semantical Point-Voxel Feature Interaction for 3D Object Detection

Peng Wu, Lipeng Gu, Xuefeng Yan +4

Large imbalance often exists between the foreground points (i.e., objects) and the background points in outdoor LiDAR point clouds. It hinders cutting-edge detectors from focusing…