Remote sensing (RS) imagery provides invaluable insights into characterizing the Earth's
land surface within the scope of Earth observation (EO). Technological advances in capture …

As an important component of intelligent transportation systems, collaborative perception
has made great progress in recent years. In collaborative perception, multiple devices rely …

In this work, we seek to predict camera poses across scenes with a multi-task learning
manner, where we view the localization of each scene as a new task. We propose OFVL …

We present CO-Net, a cohesive framework that optimizes multiple point cloud tasks
collectively across heterogeneous dataset domains. CO-Net maintains the characteristics of …

In this work, we seek to learn multiple mainstream vision tasks concurrently using a unified
network, which is storage-efficient as numerous networks with task-shared parameters can …

In recent years, significant progress has been witnessed in the field of deep learning-based
object detection. As a subtask in the field of object detection, traffic sign detection has great …

Recently, scene coordinate regression (SCoRe) approaches for visual localization have
been extensively investigated. However, current SCoRe methods are scene-specific and …

Local feature matching is crucial for various computer vision tasks like Structure from Motion
(SfM) and visual localization. In human visual matching, individuals typically scan image …

Mixed-precision quantization plays a pivotal role in deploying deep neural networks in
resource-constrained environments. However, the task of finding the optimal bit-width …

Lane segmentation at night is a challenging problem in autonomous driving perception,
which is beneficial to improve the robustness of the application. Existing methods has shown …