9 citations · 13 across the 4 of their papers we have counts for
4 papers
MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation
Rajeev Yasarla, Hong Cai, Jisoo Jeong +3
We propose MAMo, a novel memory and attention frame-work for monocular video depth estimation. MAMo can augment and improve any single-image depth estimation networks into video de…
EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation
Yunxiao Shi, Hong Cai, Amin Ansari +1
The ubiquitous multi-camera setup on modern autonomous vehicles provides an opportunity to construct surround-view depth. Existing methods, however, either perform independent mono…
Self-Supervised Learning of Depth and Ego-motion with Differentiable Bundle Adjustment
Yunxiao Shi, Jing Zhu, Yi Fang +2
Learning to predict scene depth and camera motion from RGB inputs only is a challenging task. Most existing learning based methods deal with this task in a supervised manner which…
Structure-Attentioned Memory Network for Monocular Depth Estimation
Jing Zhu, Yunxiao Shi, Mengwei Ren +3
Monocular depth estimation is a challenging task that aims to predict a corresponding depth map from a given single RGB image. Recent deep learning models have been proposed to pre…