9 accepted papers
World models are critical for autonomous driving to simulate environmental dynamics and generate synthetic data. Existing methods struggle to disentangle ego-vehicle motion (perspective shifts) from scene evolvement (agent interactions), leading to suboptimal predictions. Instead, we propose to sepa…
Recent advancements have underscored the exceptional analytical and situational understanding capabilities of Large Language Models (LLMs) in autonomous driving decisions. However, the inherent hallucination issues of LLMs pose significant safety concerns when utilized as standalone decision-making…
We propose a novel motion-based tracker specifically designed for tracking multiple people in low frame rate scenarios. While previous studies have predominantly focused on scenarios with high frame rates (exceeding 10 frames per second), tracking in low frame rate conditions is significant for robo
Electrocardiogram (ECG) is essential for the early prevention and diagnosis of cardiovascular diseases. The rise of wearable ECG devices has facilitated high-precision heart rate detection, enabling early interventions. Advances in Artificial Neural Networks (ANNs), particularly One-Dimensional Conv…
Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object detection are mostly based on feature imitation. In this paper we present a general and effective prediction mimicking dis…
Vision-and-Language Navigation (VLN) has garnered widespread attention and research interest due to its potential applications in real-world scenarios. Despite significant progress in the VLN field in recent years, limitations persist. Many agents struggle to make accurate decisions when faced with
Occupancy prediction, aiming at predicting the occupancy status within voxelized 3D environment, is quickly gaining momentum within the autonomous driving community. Mainstream occupancy prediction works first discretize the 3D environment into voxels, then perform classification on such dense grids…
"In autonomous driving, the temporal stability of 3D object detection greatly impacts the driving safety. However, the detection stability cannot be accessed by existing metrics such as mAP and MOTA, and consequently is less explored by the community. To bridge this gap, this work proposes (), a new…
Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes. This diminishes the detectors' speed, thereby becoming the computational bottleneck in advanced oriented object detection systems. This work proposes an effective and simple oriented object detec…