3 citations · 6 across the 15 of their papers we have counts for
15 papers
StampFormer: A Physics-Guided Material-Geometry-Coupled Multimodal Model for Rapid Prediction of Physical Fields in Sheet Metal Stamping
Jiajie Luo, Mohamed Mohamed, Osama Hassan +8
Traditional sheet metal forming relies on time-consuming and expensive Finite Element Analysis (FEA) for design validation, a process that significantly prolongs design cycles. Whi…
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…
Reusing Attention for One-stage Lane Topology Understanding
Yang Li, Zongzheng Zhang, Xuchong Qiu +10
Understanding lane toplogy relationships accurately is critical for safe autonomous driving. However, existing two-stage methods suffer from inefficiencies due to error propagation…
Control Map Distribution using Map Query Bank for Online Map Generation
Ziming Liu, Leichen Wang, Ge Yang +4
Reliable autonomous driving systems require high-definition (HD) map that contains detailed map information for planning and navigation. However, pre-build HD map requires a large…
Chameleon: Fast-slow Neuro-symbolic Lane Topology Extraction
Zongzheng Zhang, Xinrun Li, Sizhe Zou +8
Lane topology extraction involves detecting lanes and traffic elements and determining their relationships, a key perception task for mapless autonomous driving. This task requires…
3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion
Pengru Deng, Jiapeng Yao, Chun Li +4
Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse scenarios, exhibits limited rob…
PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentation
Shoumeng Qiu, Xinrun Li, XiangYang Xue +1
Although multiview fusion has demonstrated potential in LiDAR segmentation, its dependence on computationally intensive point-based interactions, arising from the lack of fixed cor…
Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic Segmentation
Shoumeng Qiu, Jie Chen, Xinrun Li +3
In this paper, we introduce a novel knowledge distillation approach for the semantic segmentation task. Unlike previous methods that rely on power-trained teachers or other modalit…
Towards Camera Open-set 3D Object Detection for Autonomous Driving Scenarios
Zhuolin He, Xinrun Li, Jiacheng Tang +4
Conventional camera-based 3D object detectors in autonomous driving are limited to recognizing a predefined set of objects, which poses a safety risk when encountering novel or uns…
Sensor Visibility Estimation: Metrics and Methods for Systematic Performance Evaluation and Improvement
Joachim Börger, Marc Patrick Zapf, Marat Kopytjuk +2
Sensor visibility is crucial for safety-critical applications in automotive, robotics, smart infrastructure and others: In addition to object detection and occupancy mapping, visib…