Are we ready for vision-centric driving streaming perception? the asap benchmark
In recent years, vision-centric perception has flourished in various autonomous driving tasks,
including 3D detection, semantic map construction, motion forecasting, and depth …
including 3D detection, semantic map construction, motion forecasting, and depth …
FADM-SLAM: A fast and accurate dynamic intelligent motion SLAM for autonomous robot exploration involving movable objects
Purpose Many popular simultaneous localization and mapping (SLAM) techniques have low
accuracy, especially when localizing environments containing dynamically moving objects …
accuracy, especially when localizing environments containing dynamically moving objects …
Mono-ViFI: A Unified Learning Framework for Self-supervised Single and Multi-frame Monocular Depth Estimation
Self-supervised monocular depth estimation has gathered notable interest since it can
liberate training from dependency on depth annotations. In monocular video training case …
liberate training from dependency on depth annotations. In monocular video training case …
M Depth: Self-supervised Two-Frame Multi-camera Metric Depth Estimation
This paper presents a novel self-supervised two-frame multi-camera metric depth estimation
network, termed M\({^ 2}\) Depth, which is designed to predict reliable scale-aware …
network, termed M\({^ 2}\) Depth, which is designed to predict reliable scale-aware …
Self-Supervised Monocular Depth Estimation With Positional Shift Depth Variance and Adaptive Disparity Quantization
Recently, attempts to learn the underlying 3D structures of a scene from monocular videos in
a fully self-supervised fashion have drawn much attention. One of the most challenging …
a fully self-supervised fashion have drawn much attention. One of the most challenging …
Self-supervised multi-frame depth estimation with visual-inertial pose transformer and monocular guidance
Self-supervised monocular depth estimation has been a popular topic since it does not need
labor-intensive depth ground truth collection. However, the accuracy of monocular network …
labor-intensive depth ground truth collection. However, the accuracy of monocular network …
Monocular depth estimation via self-supervised self-distillation
Self-supervised monocular depth estimation can exhibit excellent performance in static
environments due to the multi-view consistency assumption during the training process …
environments due to the multi-view consistency assumption during the training process …
Exploring the mutual influence between self-supervised single-frame and multi-frame depth estimation
J Xiang, Y Wang, L An, H Liu… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Although both self-supervised single-frame and multi-frame depth estimation methods only
require unlabeled monocular videos for training, the information they leverage varies …
require unlabeled monocular videos for training, the information they leverage varies …
SIM-MultiDepth: Self-Supervised Indoor Monocular Multi-Frame Depth Estimation Based on Texture-Aware Masking
Self-supervised monocular depth estimation methods have become the focus of research
since ground truth data are not required. Current single-image-based works only leverage …
since ground truth data are not required. Current single-image-based works only leverage …
Exploring Few-Beam LiDAR Assistance in Self-Supervised Multi-Frame Depth Estimation
Self-supervised multi-frame depth estimation methods only require unlabeled monocular
videos for training. However, most existing methods face challenges, including accuracy …
videos for training. However, most existing methods face challenges, including accuracy …