no code implementations • 22 Nov 2023 • Yaqi Liu, Chao Xia, Song Xiao, Qingxiao Guan, Wenqian Dong, Yifan Zhang, Nenghai Yu
In this paper, we propose a Transformer-style copy-move forgery detection network named as CMFDFormer, and provide a novel PCSD (Pooled Cube and Strip Distillation) continual learning framework to help CMFDFormer handle new tasks.
no code implementations • 27 Apr 2023 • Chao Xia, Chenfeng Xu, Patrick Rim, Mingyu Ding, Nanning Zheng, Kurt Keutzer, Masayoshi Tomizuka, Wei Zhan
Current LiDAR odometry, mapping and localization methods leverage point-wise representations of 3D scenes and achieve high accuracy in autonomous driving tasks.
1 code implementation • 16 Dec 2020 • Yaqi Liu, Chao Xia, Xiaobin Zhu, Shengwei Xu
The first stage is a backbone self deep matching network, and the second stage is named as Proposal SuperGlue.
no code implementations • 16 Nov 2019 • Pengyu Gao, Siyu Xia, Joseph Robinson, Junkang Zhang, Chao Xia, Ming Shao, Yun Fu
Specifically, we propose a two-stage kin-face generation model to predict the appearance of a child given a pair of parents.