7 accepted papers
Spiking Neural Networks (SNNs) often rely on rate coding, where high-precision inference depends on long time-steps, leading to significant latency and energy cost—especially for ANN-to-SNN conversions. To address this, we propose Adaptive Fission, a post-training encoding technique that selectively…
Large language models (LLMs) have been able to perform various forms of reasoning tasks ina wide range of scenarios, but are they truly engaging in task abstraction and rule-based reasoning beyond mere memorization? To answer this question, we propose a novel experimentalapproach, Misleading Fine-Tu
Spiking neural networks (SNNs) are energy-efficient and hold great potential for large-scale inference. Since training SNNs from scratch is costly and has limited performance, converting pretrained artificial neural networks (ANNs) to SNNs is an attractive approach that retains robust performance wi…
Multiple sensors, especially cameras and LiDARs, are widely used in autonomous vehicles. In order to fuse data from different sensors accurately, precise calibrations are required, including camera intrinsic parameters, and relative poses between multiple cameras and LiDARs. However, most existing c…
LiDAR map matching(LMM) is a critical localization technique in autonomous driving while existing methods have problems in terms of both accuracy and robustness when driving in the scenes with poor structure information (e.g. highways). This paper put forward a multi-level intensity map based cascad…
Estimating the 6-DoF camera pose of an image with respect to a 3D scene model, known as visual localization, is a fundamental problem in many computer vision and robotics tasks. Among various visual localization methods, the direct 2D-3D matching method has become the preferred method for many pract…
Compared to widely used LiDAR-based mapping in autonomous driving field, image-based mapping method has the advantages of low cost, high resolution, and no need for complex calibration. However, the image-based 3D mapping depends heavily on the texture richness and always leaves holes and outliers i…