5 accepted papers
Monocular 3D object detection has received growing recognition in contemporary research due to its reduced hardware complexity and lower deployment cost compared to multi-sensor-based approaches. Prior research has primarily addressed ideal environmental settings, neglecting the influence of diverse…
Monocular 3D object detection has gained attention for its cost-efficiency and simpler setup compared to multi-sensor systems. In this task, accurate depth estimation is crucial for precise object localization, yet extracting sufficient depth cues from a single image remains inherently challenging. …
A multimodal fusion technique using LiDAR-camera has been developed for precise 3D object detection in autonomous driving and provides acceptable detection performance in ideal conditions with clear weather. However, the existing multimodal methods are still vulnerable to adverse weather conditions,…
The development of a multimodal fusion technique utilizing LiDAR-camera data has enabled precise 3D object detection for self-driving vehicles, particularly in ideal conditions with clear weather. Nevertheless, adverse weathers such as fog, snow, and rain remain a challenge for existing multimodal m
Adversarial attacks pose a severe threat to the accuracy of person re-identification (re-ID) systems, a critical security technology. Adversarial purification methods are promising approaches for defending against comprehensive attacks, including unseen ones. However, re-ID testing identities (IDs)…