1 code implementation • 22 Nov 2022 • Mingjia Li, Binhui Xie, Shuang Li, Chi Harold Liu, Xinjing Cheng
However, previous methods often reckon on additional reference images of the same scenes taken from normal conditions, which are quite tough to collect in reality.
Ranked #7 on Domain Adaptation on Cityscapes to ACDC
1 code implementation • 2 Dec 2021 • Binhui Xie, Longhui Yuan, Shuang Li, Chi Harold Liu, Xinjing Cheng, Guoren Wang
Unsupervised domain adaptation has recently emerged as an effective paradigm for generalizing deep neural networks to new target domains.
1 code implementation • CVPR 2022 • Binhui Xie, Longhui Yuan, Shuang Li, Chi Harold Liu, Xinjing Cheng
Self-training has greatly facilitated domain adaptive semantic segmentation, which iteratively generates pseudo labels on unlabeled target data and retrains the network.
1 code implementation • 11 May 2021 • Shuang Li, Binhui Xie, Bin Zang, Chi Harold Liu, Xinjing Cheng, Ruigang Yang, Guoren Wang
Specifically, we first design a pixel-wise contrastive loss by considering the correspondences between semantic distributions and pixel-wise representations from both domains.
1 code implementation • CVPR 2021 • Shuang Li, Kaixiong Gong, Chi Harold Liu, Yulin Wang, Feng Qiao, Xinjing Cheng
Real-world training data usually exhibits long-tailed distribution, where several majority classes have a significantly larger number of samples than the remaining minority classes.
Ranked #2 on Long-tail Learning on CIFAR-100-LT (ρ=200)
no code implementations • ECCV 2020 • Yuexin Ma, Xinge ZHU, Xinjing Cheng, Ruigang Yang, Jiming Liu, Dinesh Manocha
Then we aggregate dynamic points to instance points, which stand for moving objects such as pedestrians in videos.
no code implementations • 3 Jul 2020 • Xinjing Cheng, Peng Wang, Yanqi Zhou, Chenye Guan, Ruigang Yang
Omnidirectional 360{\deg} camera proliferates rapidly for autonomous robots since it significantly enhances the perception ability by widening the field of view(FoV).
no code implementations • 13 Nov 2019 • Xinjing Cheng, Peng Wang, Chenye Guan, Ruigang Yang
In this paper, we propose CSPN++, which further improves its effectiveness and efficiency by learning adaptive convolutional kernel sizes and the number of iterations for the propagation, thus the context and computational resources needed at each pixel could be dynamically assigned upon requests.
no code implementations • 27 Nov 2018 • Qichuan Geng, Hong Zhang, Xinyu Huang, Sen Wang, Feixiang Lu, Xinjing Cheng, Zhong Zhou, Ruigang Yang
As it is labor-intensive to annotate semantic parts on real street views, we propose a specific approach to implicitly transfer part features from synthesized images to real street views.
1 code implementation • 4 Oct 2018 • Xinjing Cheng, Peng Wang, Ruigang Yang
In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for various depth estimation tasks.
1 code implementation • ECCV 2018 • Xinjing Cheng, Peng Wang, Ruigang Yang
Depth estimation from a single image is a fundamental problem in computer vision.
2 code implementations • 16 Mar 2018 • Xinyu Huang, Peng Wang, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, Ruigang Yang
In this paper, we provide a sensor fusion scheme integrating camera videos, consumer-grade motion sensors (GPS/IMU), and a 3D semantic map in order to achieve robust self-localization and semantic segmentation for autonomous driving.