Abstract Multimodal Visual Object Tracking (VOT) has recently gained significant attention
due to its robustness. Early research focused on fully fine-tuning RGB-based trackers which …

In the realm of video object tracking auxiliary modalities such as depth thermal or event data
have emerged as valuable assets to complement the RGB trackers. In practice most existing …

Most nighttime semantic segmentation studies are based on domain adaptation approaches
and image input. However, limited by the low dynamic range of conventional cameras …

We present DFormer, a novel RGB-D pretraining framework to learn transferable
representations for RGB-D segmentation tasks. DFormer has two new key innovations: 1) …

Multi-modal semantic segmentation significantly enhances AI agents' perception and scene
understanding, especially under adverse conditions like low-light or overexposed …

Dense prediction tasks, such as semantic segmentation, depth estimation, and surface
normal prediction, can be easily formulated as per-pixel classification (discrete outputs) or …

We present the first publicly-available RGB-thermal dataset designed for aerial robotics
operating in natural environments. Our dataset captures a variety of terrain across the United …

Wide-range multiscale object detection for multispectral scene perception from a drone
perspective is challenging. Previous RGB-T perception methods directly use backbone …

In recent years, there has been significant progress in employing color images for anomaly
detection in industrial scenarios, but it is insufficient for identifying anomalies that are …

In real-world scenarios, the information quality provided by RGB and thermal (RGB-T)
sensors often varies across samples. This variation will negatively impact the performance of …