no code implementations • 17 Mar 2024 • Baolu Li, Jinlong Li, Xinyu Liu, Runsheng Xu, Zhengzhong Tu, Jiacheng Guo, Xiaopeng Li, Hongkai Yu
Current LiDAR-based Vehicle-to-Everything (V2X) multi-agent perception systems have shown the significant success on 3D object detection.
no code implementations • 13 Mar 2024 • Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda, Haifeng Qian, Hantian Ding, Qing Sun, Jun Wang, Jiacheng Guo, Liangfu Chen, Parminder Bhatia, Ramesh Nallapati, Sudipta Sengupta, Bing Xiang
In our study, we present bifurcated attention, a method developed for language model inference in single-context batch sampling contexts.
no code implementations • 8 Mar 2024 • Huiming Sun, Jiacheng Guo, Zibo Meng, Tianyun Zhang, Jianwu Fang, Yuewei Lin, Hongkai Yu
One white-box and two black-box patch based attack methods are implemented to attack three classic deep neural networks based object detectors on EVD4UAV.
no code implementations • 6 Jul 2023 • Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai
This paper studies the sample-efficiency of learning in Partially Observable Markov Decision Processes (POMDPs), a challenging problem in reinforcement learning that is known to be exponentially hard in the worst-case.
no code implementations • 21 Jun 2023 • Jiacheng Guo, Zihao Li, Huazheng Wang, Mengdi Wang, Zhuoran Yang, Xuezhou Zhang
In this paper, we study representation learning in partially observable Markov Decision Processes (POMDPs), where the agent learns a decoder function that maps a series of high-dimensional raw observations to a compact representation and uses it for more efficient exploration and planning.
no code implementations • ICCV 2023 • Sha Meng, Dian Shao, Jiacheng Guo, Shan Gao
Unsupervised learning is a challenging task due to the lack of labels.
no code implementations • 16 Jan 2021 • Nuo Xu, Chunlei Huo, Jiacheng Guo, Yiwei Liu, Jian Wang, Chunhong Pan
In recent years, deep learning methods bring incredible progress to the field of object detection.