Beyond Object Recognition: A New Benchmark towards Object Concept Learning

no code implementations • ICCV 2023 • Yong-Lu Li, Yue Xu, Xinyu Xu, Xiaohan Mao, Yuan YAO, SiQi Liu, Cewu Lu

To support OCL, we build a densely annotated knowledge base including extensive labels for three levels of object concept (category, attribute, affordance), and the causal relations of three levels.

Attribute Object +1

PAI3D: Painting Adaptive Instance-Prior for 3D Object Detection

no code implementations • 15 Nov 2022 • Hao liu, Zhuoran Xu, Dan Wang, Baofeng Zhang, Guan Wang, Bo Dong, Xin Wen, Xinyu Xu

3D object detection is a critical task in autonomous driving.

3D Object Detection Autonomous Driving +4

Learning to Anticipate Future with Dynamic Context Removal

1 code implementation • CVPR 2022 • Xinyu Xu, Yong-Lu Li, Cewu Lu

Anticipating future events is an essential feature for intelligent systems and embodied AI.

Learning Single/Multi-Attribute of Object with Symmetry and Group

1 code implementation • 9 Oct 2021 • Yong-Lu Li, Yue Xu, Xinyu Xu, Xiaohan Mao, Cewu Lu

To model the compositional nature of these concepts, it is a good choice to learn them as transformations, e. g., coupling and decoupling.

Attribute Compositional Zero-Shot Learning

Multi-modal Trajectory Prediction for Autonomous Driving with Semantic Map and Dynamic Graph Attention Network

no code implementations • 30 Mar 2021 • Bo Dong, Hao liu, Yu Bai, Jinbiao Lin, Zhuoran Xu, Xinyu Xu, Qi Kong

Predicting future trajectories of surrounding obstacles is a crucial task for autonomous driving cars to achieve a high degree of road safety.

Autonomous Driving Graph Attention +1