no code implementations • 18 Apr 2024 • Yuzhu Cai, Sheng Yin, Yuxi Wei, Chenxin Xu, Weibo Mao, Felix Juefei-Xu, Siheng Chen, Yanfeng Wang
The burgeoning landscape of text-to-image models, exemplified by innovations such as Midjourney and DALLE 3, has revolutionized content creation across diverse sectors.
1 code implementation • 15 Apr 2024 • Genjia Liu, Yue Hu, Chenxin Xu, Weibo Mao, Junhao Ge, Zhengxiang Huang, Yifan Lu, Yinda Xu, Junkai Xia, Yafei Wang, Siheng Chen
This effort necessitates two key foundations: a platform capable of generating data to facilitate the training and testing of V2X-AD, and a comprehensive system that integrates full driving-related functionalities with mechanisms for information sharing.
no code implementations • 11 Sep 2023 • Chunyong Hu, Hang Zheng, Kun Li, Jianyun Xu, Weibo Mao, Maochun Luo, Lingxuan Wang, Mingxia Chen, Qihao Peng, Kaixuan Liu, Yiru Zhao, Peihan Hao, Minzhe Liu, Kaicheng Yu
Multi-sensor modal fusion has demonstrated strong advantages in 3D object detection tasks.
1 code implementation • ICCV 2023 • Qingyao Xu, Weibo Mao, Jingze Gong, Chenxin Xu, Siheng Chen, Weidi Xie, Ya zhang, Yanfeng Wang
Multi-person motion prediction is a challenging problem due to the dependency of motion on both individual past movements and interactions with other people.
1 code implementation • 2 Aug 2023 • Tengju Ye, Wei Jing, Chunyong Hu, Shikun Huang, Lingping Gao, Fangzhen Li, Jingke Wang, Ke Guo, Wencong Xiao, Weibo Mao, Hang Zheng, Kun Li, Junbo Chen, Kaicheng Yu
Building a multi-modality multi-task neural network toward accurate and robust performance is a de-facto standard in perception task of autonomous driving.
1 code implementation • CVPR 2023 • Weibo Mao, Chenxin Xu, Qi Zhu, Siheng Chen, Yanfeng Wang
The core of the proposed LED is to leverage a trainable leapfrog initializer to directly learn an expressive multi-modal distribution of future trajectories, which skips a large number of denoising steps, significantly accelerating inference speed.
1 code implementation • CVPR 2022 • Chenxin Xu, Weibo Mao, Wenjun Zhang, Siheng Chen
However, in this way, the model parameters come from all seen instances, which means a huge amount of irrelevant seen instances might also involve in predicting the current situation, disturbing the performance.
Ranked #7 on Trajectory Prediction on Stanford Drone