Search Results for author: Chenjie Wang

Found 6 papers, 0 papers with code

CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks

no code implementations4 Apr 2024 Beibei Wang, Lu Zhang, Shuang Meng, Chenjie Wang, Jingjing Huang, Yao Li, Haojie Ren, Yuxuan Xiao, Yuru Peng, Jianmin Ji, Yu Zhang, Yanyong Zhang

Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems research and development.

Autonomous Driving Instance Segmentation +1

RiWNet: A moving object instance segmentation Network being Robust in adverse Weather conditions

no code implementations4 Sep 2021 Chenjie Wang, Chengyuan Li, Bin Luo, Wei Wang, Jun Liu

Then we extend SOLOV2 to capture temporal information in video to learn motion information, and propose a moving object instance segmentation network with RiWFPN called RiWNet.

Instance Segmentation Segmentation +1

Object Detection based on OcSaFPN in Aerial Images with Noise

no code implementations18 Dec 2020 Chengyuan Li, Jun Liu, Hailong Hong, Wenju Mao, Chenjie Wang, Chudi Hu, Xin Su, Bin Luo

On the basis of this, a novel octave convolution-based semantic attention feature pyramid network (OcSaFPN) is proposed to get higher accuracy in object detection with noise.

Attribute Denoising +2

Vestigial anyon condensation in kagome quantum spin liquids

no code implementations31 Aug 2020 Yan-Cheng Wang, Zheng Yan, Chenjie Wang, Yang Qi, Zi Yang Meng

We construct a lattice model of topological order (kagome quantum spin liquids) and solve it with unbiased quantum Monte Carlo simulations.

Strongly Correlated Electrons

U2-ONet: A Two-level Nested Octave U-structure with Multiscale Attention Mechanism for Moving Instances Segmentation

no code implementations26 Jul 2020 Chenjie Wang, Chengyuan Li, Bin Luo

Most scenes in practical applications are dynamic scenes containing moving objects, so segmenting accurately moving objects is crucial for many computer vision applications.

DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation

no code implementations10 Mar 2020 Chenjie Wang, Bin Luo, Yun Zhang, Qing Zhao, Lu Yin, Wei Wang, Xin Su, Yajun Wang, Chengyuan Li

The only input of DymSLAM is stereo video, and its output includes a dense map of the static environment, 3D model of the moving objects and the trajectories of the camera and the moving objects.

Motion Segmentation

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