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Kun Tang

4 accepted papers

2024

MAPLM: A Real-World Large-Scale Vision-Language Benchmark for Map and Traffic Scene Understanding

CVPR 2024poster

Vision-language generative AI has demonstrated remarkable promise for empowering cross-modal scene understanding of autonomous driving and high-definition (HD) map systems. However current benchmark datasets lack multi-modal point cloud image and language data pairs. Recent approaches utilize visual…

2023

Flexible 3D Lane Detection by Hierarchical Shape Matching

AAAI 2023technical

As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict demands for precision. In this paper, an end-to-end flexible and hierarchical lane detector is proposed to precisely predi…

2023

Mitigating Transformer Overconfidence via Lipschitz Regularization

UAI 2023poster

Though Transformers have achieved promising results in many computer vision tasks, they tend to be over-confident in predictions, as the standard Dot Product Self-Attention (DPSA) can barely preserve distance for the unbounded input domain. In this work, we fill this gap by proposing a novel Lipschi…

2023

THMA: Tencent HD Map AI System for Creating HD Map Annotations

AAAI 2023technical

Nowadays, autonomous vehicle technology is becoming more and more mature. Critical to progress and safety, high-definition (HD) maps, a type of centimeter-level map collected using a laser sensor, provide accurate descriptions of the surrounding environment. The key challenge of HD map production is…

Cited by 13SourcePDFScholar