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20242026
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cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…