1 code implementation • 12 Mar 2024 • Chunlong Xia, Xinliang Wang, Feng Lv, Xin Hao, Yifeng Shi
Compared to the state-of-the-art, ViT-CoMer has the following advantages: (1) We inject spatial pyramid multi-receptive field convolutional features into the ViT architecture, which effectively alleviates the problems of limited local information interaction and single-feature representation in ViT.
1 code implementation • 22 Dec 2023 • Zhenjia Li, Jinrang Jia, Yifeng Shi
To select samples adaptively, we propose a Learnable Sample Selection (LSS) module, which is based on Gumbel-Softmax and a relative-distance sample divider.
Ranked #2 on Monocular 3D Object Detection on KITTI Cars Moderate
1 code implementation • 12 Oct 2023 • Xianghao Kong, Wentao Jiang, Jinrang Jia, Yifeng Shi, Runsheng Xu, Si Liu
To take full advantage of simulated data, we present a new unsupervised sim2real domain adaptation method for V2X collaborative detection named Decoupled Unsupervised Sim2Real Adaptation (DUSA).
1 code implementation • CVPR 2023 • Haibao Yu, Wenxian Yang, Hongzhi Ruan, Zhenwei Yang, Yingjuan Tang, Xu Gao, Xin Hao, Yifeng Shi, Yifeng Pan, Ning Sun, Juan Song, Jirui Yuan, Ping Luo, Zaiqing Nie
Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of surrounding traffic participants can significantly improve decision-making and safety in autonomous driving.
no code implementations • 4 May 2023 • Yifeng Shi, Marc Niethammer
To answer 2), we propose novel scores that summarize the learned common and individual structures and visualize the score gradients with respect to the input, visually discerning what the different representations capture.
1 code implementation • 12 Apr 2023 • Yifeng Shi, Feng Lv, Xinliang Wang, Chunlong Xia, Shaojie Li, Shujie Yang, Teng Xi, Gang Zhang
To address these, we designed the 1st Foundation Model Challenge, with the goal of increasing the popularity of foundation model technology in traffic scenarios and promoting the rapid development of the intelligent transportation industry.
Ranked #1 on 2D Object Detection on CeyMo
1 code implementation • ICCV 2023 • Zhijie Yan, Pengfei Li, Zheng Fu, Shaocong Xu, Yongliang Shi, Xiaoxue Chen, Yuhang Zheng, Yang Li, Tianyu Liu, Chuxuan Li, Nairui Luo, Xu Gao, Yilun Chen, Zuoxu Wang, Yifeng Shi, Pengfei Huang, Zhengxiao Han, Jirui Yuan, Jiangtao Gong, Guyue Zhou, Hang Zhao, Hao Zhao
One of the most challenging problems in motion forecasting is interactive trajectory prediction, whose goal is to jointly forecasts the future trajectories of interacting agents.
no code implementations • ICCV 2023 • Ziming Chen, Yifeng Shi, Jinrang Jia
Furthermore, it can align the domain gaps between vehicle and infrastructure features, and improve the robustness of feature fusion, leading to a high cooperative perception accuracy.
no code implementations • 17 Oct 2022 • Longrui Chen, Yan Zhang, Wenjie Jiang, Jiangtao Gong, Jiahao Shen, Mengdi Chu, Chuxuan Li, Yifeng Pan, Yifeng Shi, Nairui Luo, Xu Gao, Jirui Yuan, Guyue Zhou, Yaqin Zhang
This paper proposes a high-fidelity simulation framework that can estimate the potential safety benefits of vehicle-to-infrastructure (V2I) pedestrian safety strategies.
1 code implementation • CVPR 2022 • Haibao Yu, Yizhen Luo, Mao Shu, Yiyi Huo, Zebang Yang, Yifeng Shi, Zhenglong Guo, Hanyu Li, Xing Hu, Jirui Yuan, Zaiqing Nie
Autonomous driving faces great safety challenges for a lack of global perspective and the limitation of long-range perception capabilities.
no code implementations • 25 Mar 2022 • Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding
On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.
no code implementations • CVPR 2022 • Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding
On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.
1 code implementation • 25 May 2021 • Wenhao Wu, Yuxiang Zhao, Yanwu Xu, Xiao Tan, Dongliang He, Zhikang Zou, Jin Ye, YingYing Li, Mingde Yao, ZiChao Dong, Yifeng Shi
Long-range and short-range temporal modeling are two complementary and crucial aspects of video recognition.
Ranked #6 on Action Recognition on ActivityNet
no code implementations • 7 Jun 2020 • Yifeng Shi, Christopher M. Bender, Junier B. Oliva, Marc Niethammer
Clustering and prediction are two primary tasks in the fields of unsupervised and supervised learning, respectively.
no code implementations • ICML 2020 • Christopher M. Bender, Yang Li, Yifeng Shi, Michael K. Reiter, Junier B. Oliva
In this work we develop a novel Bayesian neural network methodology to achieve strong adversarial robustness without the need for online adversarial training.
no code implementations • 21 Sep 2019 • Yifeng Shi, Junier Oliva, Marc Niethammer
DMPS not only connects learning on graphs with learning on sets via deep kernel learning, but it also bridges message passing on sets and traditional diffusion dynamics commonly used in denoising models.