activity
20182020
most citedIPOD: Intensive Point-based Object Detector for Point Cloud

132 citations · 401 across the 9 of their papers we have counts for

collaborators

20 papers

cs.CV202011 cited

Tensor Low-Rank Reconstruction for Semantic Segmentation

Wanli Chen, Xinge Zhu, Ruoqi Sun +4

Context information plays an indispensable role in the success of semantic segmentation. Recently, non-local self-attention based methods are proved to be effective for context inf…

cs.CV2020

DSGN: Deep Stereo Geometry Network for 3D Object Detection

Yilun Chen, Shu Liu, Xiaoyong Shen +1

Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods. It is caused by the wa…

cs.CV20197 cited

An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation

Jihan Yang, Ruijia Xu, Ruiyu Li +4

We focus on Unsupervised Domain Adaptation (UDA) for the task of semantic segmentation. Recently, adversarial alignment has been widely adopted to match the marginal distribution o…

cs.CV201932 cited

Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation

Li Jiang, Hengshuang Zhao, Shu Liu +3

We achieve 3D semantic scene labeling by exploring semantic relation between each point and its contextual neighbors through edges. Besides an encoder-decoder branch for predicting…

cs.CV2019

Reflective Decoding Network for Image Captioning

Lei Ke, Wenjie Pei, Ruiyu Li +2

State-of-the-art image captioning methods mostly focus on improving visual features, less attention has been paid to utilizing the inherent properties of language to boost captioni…

cs.CV2019

Non-local Recurrent Neural Memory for Supervised Sequence Modeling

Canmiao Fu, Wenjie Pei, Qiong Cao +4

Typical methods for supervised sequence modeling are built upon the recurrent neural networks to capture temporal dependencies. One potential limitation of these methods is that th…