17 accepted papers
Using unmanned aerial vehicle (UAV) formations to guide unmanned ground vehicles (UGVs) through unstructured obstacle-laden areas leads to highly efficient execution of tasks such as the transportation of supplies. However, existing methods fail to efficiently plan obstacle-avoidance strategies for …
We present Eve3D, a novel framework for dense 3D reconstruction based on 3D Gaussian Splatting (3DGS). While most existing methods rely on imperfect priors derived from pre-trained vision models, Eve3D fully leverages these priors by jointly optimizing both them and the 3DGS backbone. This joint opt…
Reconstructing accurate surfaces with radiance fields has achieved remarkable progress in recent years. However, prevailing approaches, primarily based on Gaussian Splatting, are increasingly constrained by representational bottlenecks. In this paper, we introduce GeoSVR, an explicit voxel-based fra…
NeRF-based SLAM has recently achieved promising results in tracking and reconstruction. However, existing methods face challenges in providing sufficient scene representation, capturing structural information, and maintaining global consistency in scenes emerging significant movement or being forgot
This work addresses the challenge of streamed video depth estimation, which expects not only per-frame accuracy but, more importantly, cross-frame consistency. We argue that sharing contextual information between frames or clips is pivotal in fostering temporal consistency. Therefore, we reformulate…
We present LightStereo, a cutting-edge stereomatching network crafted to accelerate the matching process. Departing from conventional methodologies that rely on aggregating computationally intensive 4D costs, LightStereo adopts the 3D cost volume as a lightweight alternative. While similar approache
Using unmanned aerial vehicle (UAV) formations to guide unmanned ground vehicles (UGVs) through unstructured obstacle-laden areas leads to highly efficient execution of tasks such as the transportation of supplies. However, existing methods fail to efficiently plan obstacle-avoidance strategies for
This letter presents a safety trajectory planning and tracking architecture for a quadrotor autopilot. Motor saturation constraints are explicitly considered in obstacle avoidance mission. Two challenging cases are covered: agile flight with a short task time and stable flight with actuator degradat
Given sparse depths and the corresponding RGB images, depth completion aims at spatially propagating the sparse measurements throughout the whole image to get a dense depth prediction. Despite the tremendous progress of deep-learning-based depth completion methods, the locality of the convolutional…
Neural implicit representations have recently demonstrated compelling results on dense Simultaneous Localization And Mapping (SLAM) but suffer from the accumulation of errors in camera tracking and distortion in the reconstruction. Purposely, we present GO-SLAM, a deep-learning-based dense visual SL…
We present TemporalStereo, a coarse-to-fine stereo matching network that is highly efficient, and able to effectively exploit the past geometry and context information to boost matching accuracy. Our network leverages sparse cost volume and proves to be effective when a single stereo pair is given.…
This paper is focused on the cooperative trajectory planning problem for multiple car-like robots in a cluttered and unstructured environment narrowed by static obstacles. The concerned multi-vehicle trajectory planning (MVTP) problem is challenging because i) the scenario is nonconvex and tiny; ii)…
Keyphrase Generation compresses a document into some highly-summative phrases, which is an important task in natural language processing. Most state-of-the-art adopt greedy search or beam search decoding methods. These two decoding methods generate a large number of duplicated keyphrases and are tim…
Autonomous intersection management (AIM) refers to planning the trajectories for multiple connected and automated vehicles (CAVs) when they traverse an unsignalized intersection cooperatively. As an extension of the conventional AIM, lane-free AIM allows the CAVs to adjust their velocities and paths…
This letter is focused on the time-optimal Multi-Vehicle Trajectory Planning (MVTP) problem for multiple car-like robots when they travel in a tiny indoor scenario occupied by static obstacles. Herein, the complexity of the concerned MVTP task includes i) the non-convexity and narrowness of the envi
Trajectory planning for a tractor-trailer vehicle is challenging because the vehicle kinematics consists of underactuated and nonholonomic constraints that are highly coupled. Prevalent sampling-based or search-based planners suitable for rigid-body vehicles are not capable of handling the tractor-t…
This work formulates the multi-vehicle lane change motion planning task as a centralized optimal control problem, which is beneficial in being generic and complete. However, a direct solution to this optimal control problem is numerically intractable due to the dimensionality of the collision-avoida…