3 citations · 5 across the 3 of their papers we have counts for
6 papers
Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning
Tianfang Sun, Zhizhong Zhang, Xin Tan +3
Weakly supervised point cloud semantic segmentation methods that require 1\% or fewer labels, hoping to realize almost the same performance as fully supervised approaches, which re…
Novelty Detection via Contrastive Learning with Negative Data Augmentation
Chengwei Chen, Yuan Xie, Shaohui Lin +5
Novelty detection is the process of determining whether a query example differs from the learned training distribution. Previous methods attempt to learn the representation of the…
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning
Jingyu Gong, Jiachen Xu, Xin Tan +4
Hidden features in neural network usually fail to learn informative representation for 3D segmentation as supervisions are only given on output prediction, while this can be solved…
Re-ID Driven Localization Refinement for Person Search
Chuchu Han, Jiacheng Ye, Yunshan Zhong +4
Person search aims at localizing and identifying a query person from a gallery of uncropped scene images. Different from person re-identification (re-ID), its performance also depe…
FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds
Jie Zhou, Xin Tan, Zhiwei Shao +1
3D object detection from raw and sparse point clouds has been far less treated to date, compared with its 2D counterpart. In this paper, we propose a novel framework called FVNet f…
Recurrence time correlations in random walks with preferential relocation to visited places
Daniel Campos, Vicenç Méndez
Random walks with memory typically involve rules where a preference for either revisiting or avoiding those sites visited in the past are introduced somehow. Such effects have a di…