84 citations · 260 across the 21 of their papers we have counts for
21 papers
Introspective Deep Metric Learning
Chengkun Wang, Wenzhao Zheng, Zheng Zhu +2
This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images. Conventional deep metric learning methods focus on learning…
DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving
Xiaofeng Wang, Zheng Zhu, Guan Huang +3
World models, especially in autonomous driving, are trending and drawing extensive attention due to their capacity for comprehending driving environments. The established world mod…
Multi-Prompt with Depth Partitioned Cross-Modal Learning
Yingjie Tian, Yiqi Wang, Xianda Guo +2
In recent years, soft prompt learning methods have been proposed to fine-tune large-scale vision-language pre-trained models for various downstream tasks. These methods typically c…
DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception
Jiayu Zou, Zheng Zhu, Yun Ye +1
BEV perception is of great importance in the field of autonomous driving, serving as the cornerstone of planning, controlling, and motion prediction. The quality of the BEV feature…
DiM: Distilling Dataset into Generative Model
Kai Wang, Jianyang Gu, Daquan Zhou +3
Dataset distillation reduces the network training cost by synthesizing small and informative datasets from large-scale ones. Despite the success of the recent dataset distillation…
Neural Node Matching for Multi-Target Cross Domain Recommendation
Wujiang Xu, Shaoshuai Li, Mingming Ha +5
Multi-Target Cross Domain Recommendation(CDR) has attracted a surge of interest recently, which intends to improve the recommendation performance in multiple domains (or systems) s…