14 Result(s)
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Article
Open AccessNoise4Denoise: Leveraging noise for unsupervised point cloud denoising
Existing deep learning-based point cloud denoising methods are generally trained in a supervised manner that requires clean data as ground-truth labels. However, in practice, it is not always feasible to obtai...
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Article
Veintr: robust end-to-end full-hand vein identification with transformer
Hand vein identification stands out to be an increasingly popular approach for biometric identification due to its distinctiveness and convenience. While state-of-the-art techniques are able to achieve good pe...
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Chapter and Conference Paper
TopFormer: Topology-Aware Transformer for Point Cloud Registration
The extraction of robust feature descriptors is crucial for achieving accurate point cloud registration. While the attention mechanism plays an important role in enabling sparse point features to learn global ...
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Article
Open Access3D face recognition: A comprehensive survey in 2022
In the past ten years, research on face recognition has shifted to using 3D facial surfaces, as 3D geometric information provides more discriminative features. This comprehensive survey reviews 3D face recogni...
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Article
Segmentation-driven feature-preserving mesh denoising
Feature-preserving mesh denoising has received noticeable attention in visual media, with the aim of recovering high-fidelity, clean mesh shapes from the ones that are contaminated by noise. Existing denoising...
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Article
Unsupervised contrastive learning with simple transformation for 3D point cloud data
Though a number of point cloud learning methods have been proposed to handle unordered points, most of them are supervised and require labels for training. By contrast, unsupervised learning of point cloud dat...
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Article
Open AccessTowards uniform point distribution in feature-preserving point cloud filtering
While a popular representation of 3D data, point clouds may contain noise and need filtering before use. Existing point cloud filtering methods either cannot preserve sharp features or result in uneven point d...
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Chapter and Conference Paper
CAMG: Context-Aware Moment Graph Network for Multimodal Temporal Activity Localization via Language
Temporal Activity Localization via Language (TALL) is a challenging task for language based video understanding, especially when a video contains multiple moments of interest and the language query has words d...
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Article
Open AccessApplication of evolutionary and swarm optimization in computer vision: a literature survey
Evolutionary algorithms (EAs) and swarm algorithms (SAs) have shown their usefulness in solving combinatorial and NP-hard optimization problems in various research fields. However, in the field of computer vis...
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Article
Open AccessG2MF-WA: Geometric multi-model fitting with weakly annotated data
In this paper we address the problem of geometric multi-model fitting using a few weakly annotated data points, which has been little studied so far. In weak annotating (WA), most manual annotations are suppos...
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Chapter and Conference Paper
A Cascaded Approach for Keyframes Extraction from Videos
Keyframes extraction, a fundamental problem in video processing and analysis, has remained a challenge to date. In this paper, we introduce a novel method to effectively extract keyframes of a video. It consis...
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Chapter and Conference Paper
Deep Detection for Face Manipulation
It has become increasingly challenging to distinguish real faces from their visually realistic fake counterparts, due to the great advances of deep learning based face manipulation techniques in recent years. ...
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Chapter and Conference Paper
Tag-Based Semantic Features for Scene Image Classification
The existing image feature extraction methods are primarily based on the content and structure information of images, and rarely consider the contextual semantic information. Regarding some types of images suc...
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Chapter and Conference Paper
Unsupervised Deep Features for Privacy Image Classification
Sharing images online poses security threats to a wide range of users due to the unawareness of privacy information. Deep features have been demonstrated to be a powerful representation for images. However, d...
