10 citations · 11 across the 6 of their papers we have counts for
9 papers · 1 filter
Self-Supervised Learning of Depth and Ego-Motion from Video by Alternative Training and Geometric Constraints from 3D to 2D
Jiaojiao Fang, Guizhong Liu
Self-supervised learning of depth and ego-motion from unlabeled monocular video has acquired promising results and drawn extensive attention. Most existing methods jointly train th…
Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos
Jiaojiao Fang, Guizhong Liu
Self-supervised deep learning-based 3D scene understanding methods can overcome the difficulty of acquiring the densely labeled ground-truth and have made a lot of advances. Howeve…
Trainable Class Prototypes for Few-Shot Learning
Jianyi Li, Guizhong Liu
Metric learning is a widely used method for few shot learning in which the quality of prototypes plays a key role in the algorithm. In this paper we propose the trainable prototype…
Few-Shot Image Classification via Contrastive Self-Supervised Learning
Jianyi Li, Guizhong Liu
Most previous few-shot learning algorithms are based on meta-training with fake few-shot tasks as training samples, where large labeled base classes are required. The trained model…
Unsupervised Video Depth Estimation Based on Ego-motion and Disparity Consensus
Lingtao Zhou, Jiaojiao Fang, Guizhong Liu
Unsupervised learning based depth estimation methods have received more and more attention as they do not need vast quantities of densely labeled data for training which are touch…
3D Bounding Box Estimation for Autonomous Vehicles by Cascaded Geometric Constraints and Depurated 2D Detections Using 3D Results
Jiaojiao Fang, Lingtao Zhou, Guizhong Liu
3D object detection is one of the most important tasks in 3D vision perceptual system of autonomous vehicles. In this paper, we propose a novel two stage 3D object detection method…