Qianying Ouyang — accepted AI-conference papers

2024

Crowd Perception Communication-Based Multi- Agent Path Finding With Imitation Learning

Jing Xie, Yongjun Zhang, Huanhuan Yang, Qianying Ouyang, Fang Dong, Xinyu Guo +2

RA-L 2024

Deep reinforcement learning-based Multi-Agent Path Finding (MAPF) has gained significant attention due to its remarkable adaptability to environments. Existing methods primarily leverage multi-agent communication in a fully-decentralized framework to maintain scalability while enhancing information

Cited by 2 Source ↗Scholar ↗

2024

Spatial-Aware Dynamic Lightweight Self-Supervised Monocular Depth Estimation

Linna Song, Dianxi Shi, Jianqiang Xia, Qianying Ouyang, Ziteng Qiao, Songchang Jin +1

RA-L 2024

Self-supervised monocular depth estimation has attracted extensive attention in recent years. Lightweight depth estimation methods are crucial for resource-constrained edge devices. However, existing lightweight methods often encounter the challenge of limited representation capacity and increased c

Cited by 10 Source ↗Scholar ↗