Active learning with co-auxiliary learning and multi-level diversity for image classification
Due to the fact that it is expensive and time-consuming to annotate a large amount of data,
the available labeled data to train a deep neural network is usually scarce, resulting in the …
the available labeled data to train a deep neural network is usually scarce, resulting in the …
Efficient 3D scene semantic segmentation via active learning on rendered 2D images
Inspired by Active Learning and 2D-3D semantic fusion, we proposed a novel framework for
3D scene semantic segmentation based on rendered 2D images, which could efficiently …
3D scene semantic segmentation based on rendered 2D images, which could efficiently …
Fastal: Fast evaluation module for efficient dynamic deep active learning using broad learning system
State-of-the-art Active Learning (AL) methods often encounter challenges associated with a
hysteretic learning process and an expensive data sampling mechanism. The former implies …
hysteretic learning process and an expensive data sampling mechanism. The former implies …
Active learning-based sample selection for label-efficient blind image quality assessment
Despite the considerable effort devoted to high-generalizable blind image quality
assessment (BIQA), the generalization performance of the state-of-the-art metrics remains …
assessment (BIQA), the generalization performance of the state-of-the-art metrics remains …
3D semantic segmentation of aerial photogrammetry models based on orthographic projection
Semantic segmentation of 3D scenes is one of the most important tasks in the field of
computer vision and has attracted much attention. In this paper, we propose a novel …
computer vision and has attracted much attention. In this paper, we propose a novel …
Active learning with effective scoring functions for semi-supervised temporal action localization
Abstract Temporal Action Localization (TAL) aims to predict both action category and
temporal boundary of action instances in untrimmed videos, ie, start and end time. Existing …
temporal boundary of action instances in untrimmed videos, ie, start and end time. Existing …
[引用][C] Label-Efficient Point Cloud Semantic Segmentation: A Holistic Active Learning Approach
Deep learning models are the state-of-the-arts for semantic segmentation of point clouds,
the success of which relies on the availability of large-scale annotated datasets. However, it …
the success of which relies on the availability of large-scale annotated datasets. However, it …