3 citations · 3 across the 10 of their papers we have counts for
11 papers · 1 filter
Beyond Hungarian: Match-Free Supervision for End-to-End Object Detection
Shoumeng Qiu, Xinrun Li, Yang Long
Recent DEtection TRansformer (DETR) based frameworks have achieved remarkable success in end-to-end object detection. However, the reliance on the Hungarian algorithm for bipartite…
AMap: Distilling Future Priors for Ahead-Aware Online HD Map Construction
Ruikai Li, Xinrun Li, Mengwei Xie +12
Online High-Definition (HD) map construction is pivotal for autonomous driving. While recent approaches leverage historical temporal fusion to improve performance, we identify a cr…
vMFCoOp: Towards Equilibrium on a Unified Hyperspherical Manifold for Prompting Biomedical VLMs
Minye Shao, Sihan Guo, Xinrun Li +3
Recent advances in context optimization (CoOp) guided by large language model (LLM)-distilled medical semantic priors offer a scalable alternative to manual prompt engineering and…
Learning Global Representation from Queries for Vectorized HD Map Construction
Shoumeng Qiu, Xinrun Li, Yang Long +3
The online construction of vectorized high-definition (HD) maps is a cornerstone of modern autonomous driving systems. State-of-the-art approaches, particularly those based on the…
AdaGAT: Adaptive Guidance Adversarial Training for the Robustness of Deep Neural Networks
Zhenyu Liu, Huizhi Liang, Xinrun Li +2
Adversarial distillation (AD) is a knowledge distillation technique that facilitates the transfer of robustness from teacher deep neural network (DNN) models to lightweight target…
Delving into Mapping Uncertainty for Mapless Trajectory Prediction
Zongzheng Zhang, Xuchong Qiu, Boran Zhang +11
Recent advances in autonomous driving are moving towards mapless approaches, where High-Definition (HD) maps are generated online directly from sensor data, reducing the need for e…