no code implementations • 26 Mar 2023 • Yingda Guan, Zhengyang Feng, Huiying Chang, Kuo Du, TingTing Li, Min Wang
We present SDTracker, a method that harnesses the potential of synthetic data for multi-object tracking of real-world scenes in a domain generalization and semi-supervised fashion.
1 code implementation • CVPR 2022 • Zhengyang Feng, Shaohua Guo, Xin Tan, Ke Xu, Min Wang, Lizhuang Ma
This paper presents a novel parametric curve-based method for lane detection in RGB images.
Ranked #2 on Lane Detection on LLAMAS
1 code implementation • ICCV 2021 • Qiqi Gu, Qianyu Zhou, Minghao Xu, Zhengyang Feng, Guangliang Cheng, Xuequan Lu, Jianping Shi, Lizhuang Ma
Extensive experiments demonstrate that our method can soundly boost the performance on both cross-domain object detection and segmentation for state-of-the-art techniques.
no code implementations • 15 Aug 2021 • Hongyi Xu, Fengqi Liu, Qianyu Zhou, Jinkun Hao, Zhijie Cao, Zhengyang Feng, Lizhuang Ma
Inspired by this, we propose a novel semi-supervised framework based on pseudo-labeling for outdoor 3D object detection tasks.
1 code implementation • 8 Aug 2021 • Qianyu Zhou, Zhengyang Feng, Qiqi Gu, Jiangmiao Pang, Guangliang Cheng, Xuequan Lu, Jianping Shi, Lizhuang Ma
The generated contextual mask is critical in this work and will guide the context-aware domain mixup on three different levels.
Ranked #5 on Image-to-Image Translation on SYNTHIA-to-Cityscapes
no code implementations • 19 Apr 2020 • Qianyu Zhou, Zhengyang Feng, Qiqi Gu, Guangliang Cheng, Xuequan Lu, Jianping Shi, Lizhuang Ma
Guided by this mask, we propose a ClassOut strategy to realize effective regional consistency in a fine-grained manner.
1 code implementation • 18 Apr 2020 • Zhengyang Feng, Qianyu Zhou, Qiqi Gu, Xin Tan, Guangliang Cheng, Xuequan Lu, Jianping Shi, Lizhuang Ma
Instead, leveraging inter-model disagreement between different models is a key to locate pseudo label errors.