4 code implementations • 19 Aug 2020 • Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Cong-Cong Li, Dragomir Anguelov
Our key insight is that for prediction within a moderate time horizon, the future modes can be effectively captured by a set of target states.
no code implementations • 4 Aug 2020 • Yuzhu Wu, Zhen Zhang, Gang Kou, Hengjie Zhang, Xiangrui Chao, Cong-Cong Li, Yucheng Dong, Francisco Herrera
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making.
no code implementations • CVPR 2020 • Zhishuai Zhang, Jiyang Gao, Junhua Mao, Yukai Liu, Dragomir Anguelov, Cong-Cong Li
For the Waymo Open Dataset, we achieve a bird-eyes-view (BEV) detection AP of 80. 73 and trajectory prediction average displacement error (ADE) of 33. 67cm for pedestrians, which establish the state-of-the-art for both tasks.
3 code implementations • CVPR 2020 • Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Cong-Cong Li, Cordelia Schmid
Behavior prediction in dynamic, multi-agent systems is an important problem in the context of self-driving cars, due to the complex representations and interactions of road components, including moving agents (e. g. pedestrians and vehicles) and road context information (e. g. lanes, traffic lights).
no code implementations • ECCV 2020 • Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang song, Benjamin Caine, Vijay Vasudevan, Cong-Cong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov
Data augmentation has been widely adopted for object detection in 3D point clouds.
no code implementations • ECCV 2020 • Cong-Cong Li, Dawei Du, Libo Zhang, Longyin Wen, Tiejian Luo, Yanjun Wu, Pengfei Zhu
Specifically, we first build the spatial pyramid representation to capture context information of objects at different scales.
no code implementations • 10 Apr 2019 • Cong-Cong Li, Dawei Du, Libo Zhang, Tiejian Luo, Yanjun Wu, Qi Tian, Longyin Wen, Siwei Lyu
In this paper, we propose a new data priming method to solve the domain adaptation problem.
no code implementations • 11 Dec 2016 • Jie Wang, Luyan Ji, Xiaomeng Huang, Haohuan Fu, Shiming Xu, Cong-Cong Li
Conditional probability distributions were computed based on data quality and reliability by using information selectively.
no code implementations • CVPR 2015 • Vignesh Ramanathan, Cong-Cong Li, Jia Deng, Wei Han, Zhen Li, Kunlong Gu, Yang song, Samy Bengio, Charles Rosenberg, Li Fei-Fei
Human actions capture a wide variety of interactions between people and objects.
no code implementations • NeurIPS 2011 • Cong-Cong Li, Ashutosh Saxena, Tsuhan Chen
For most scene understanding tasks (such as object detection or depth estimation), the classifiers need to consider contextual information in addition to the local features.
no code implementations • NeurIPS 2010 • Cong-Cong Li, Adarsh Kowdle, Ashutosh Saxena, Tsuhan Chen
In many machine learning domains (such as scene understanding), several related sub-tasks (such as scene categorization, depth estimation, object detection) operate on the same raw data and provide correlated outputs.