Object detection with multimodal inputs can improve many safety-critical systems such as
autonomous vehicles (AVs). Motivated by AVs that operate in both day and night, we study …

3D object detection from multiple image views is a fundamental and challenging task for
visual scene understanding. However, accurately detecting objects through perspective …

This paper presents a self-cueing real-time frame-work for attention prioritization in AI-
enabled visual perception systems that minimizes a notion of state uncertainty. By attention …

The field of autonomous driving research has made significant strides toward achieving full
automation, endowing vehicles with self-awareness and independent decision making …

We present an efficient foveal framework to perform object detection. A scale normalized
image pyramid (SNIP) is generated that, like human vision, only attends to objects within a …

Benchmarks, such as COCO, play a crucial role in object detection. However, existing
benchmarks are insufficient in scale variation, and their protocols are inadequate for fair …

Object detection is a safety-critical aspect of autonomous driving, allowing vehicles to
identify moving objects in the scene for tracking, prediction and decision making. Current …

In this report, we present our solution to the multi-task robustness track of the 1st Visual
Continual Learning (VCL) Challenge at ICCV 2023 Workshop. We propose a vanilla …

Object detection is the foundation of video query processing systems, which have been the
subject of active research in recent years. Compared to the use of a single model, model …

Cyber-physical systems (CPS) fundamentally change the way of how information systems
interact with the physical world. They integrate the sensing, computing, and communication …