Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …

In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …

Monocular depth estimation is a fundamental computer vision task. Recovering 3D depth
from a single image is geometrically ill-posed and requires scene understanding so it is not …

Understanding and reasoning about spatial relationships is crucial for Visual Question
Answering (VQA) and robotics. Vision Language Models (VLMs) have shown impressive …

This paper tackles the problem of depth estimation from a single image. Existing work either
focuses on generalization performance disregarding metric scale, ie relative depth …

Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks
in 3D perception and modeling. However the remarkable accuracy of recent MMDE methods …

Self-supervised monocular depth estimation that does not require ground truth for training
has attracted attention in recent years. It is of high interest to design lightweight but effective …

Abstract Training a Neural Radiance Field (NeRF) without pre-computed camera poses is
challenging. Recent advances in this direction demonstrate the possibility of jointly …

In this research, we propose a new 3D object detector with a trustworthy depth estimation,
dubbed BEVDepth, for camera-based Bird's-Eye-View~(BEV) 3D object detection. Our work …

Monocular depth estimation is fundamental for 3D scene understanding and downstream
applications. However, even under the supervised setup, it is still challenging and ill-posed …