Search Results for author: Xun Xu

Found 31 papers, 11 papers with code

Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering

1 code implementation6 Jun 2022 Yongyi Su, Xun Xu, Kui Jia

Test-time training (TTT) emerges as a solution to this adaptation under a realistic scenario where access to full source domain data is not available and instant inference on target domain is required.

pseudo label

SemiCurv: Semi-Supervised Curvilinear Structure Segmentation

1 code implementation18 May 2022 Xun Xu, Manh Cuong Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo

In this work, we propose SemiCurv, a semi-supervised learning (SSL) framework for curvilinear structure segmentation that is able to utilize such unlabelled data to reduce the labelling burden.

Data Augmentation

Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime

no code implementations6 May 2022 Xun Xu, Jingyi Liao, Lile Cai, Manh Cuong Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo

Recent studies combined finetuning (FT) from pretrained weights with SSL to mitigate the challenges and claimed superior results in the low-label regime.

Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning

no code implementations6 May 2022 Yongyi Su, Xun Xu, Kui Jia

Addressing the annotation challenge in 3D Point Cloud segmentation has inspired research into weakly supervised learning.

Point Cloud Segmentation Weakly Supervised 3D Point Cloud Segmentation

On Automatic Data Augmentation for 3D Point Cloud Classification

1 code implementation11 Dec 2021 Wanyue Zhang, Xun Xu, Fayao Liu, Chuan-Sheng Foo

Data augmentation is an important technique to reduce overfitting and improve learning performance, but existing works on data augmentation for 3D point cloud data are based on heuristics.

3D Object Classification 3D Object Recognition +5

Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs

no code implementations CVPR 2021 Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo

Our results strongly argue for the use of superpixel-based AL for semantic segmentation and highlight the importance of using realistic annotation costs in evaluating such methods.

Active Learning Semantic Segmentation +1

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

no code implementations9 Mar 2021 Jieneng Chen, Ke Yan, Yu-Dong Zhang, YouBao Tang, Xun Xu, Shuwen Sun, Qiuping Liu, Lingyun Huang, Jing Xiao, Alan L. Yuille, Ya zhang, Le Lu

(2) The sampled deep vertex features with positional embedding are mapped into a sequential space and decoded by a multilayer perceptron (MLP) for semantic classification.

Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach

no code implementations18 Jan 2021 Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia

Deep learning models are the state-of-the-art methods for semantic point cloud segmentation, the success of which relies on the availability of large-scale annotated datasets.

Active Learning Point Cloud Segmentation +1

Learning Category-level Shape Saliency via Deep Implicit Surface Networks

no code implementations14 Dec 2020 Chaozheng Wu, Lin Sun, Xun Xu, Kui Jia

Given the large shape variations among different instances of a same category, we are formally interested in developing a quantity defined for individual points on a continuous object surface; the quantity specifies how individual surface points contribute to the formation of the shape as the category.

Point Cloud Classification Saliency Prediction

Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer Labels

1 code implementation8 Apr 2020 Xun Xu, Gim Hee Lee

Point cloud analysis has received much attention recently; and segmentation is one of the most important tasks.

Point Cloud Segmentation

3D Rigid Motion Segmentation with Mixed and Unknown Number of Models

no code implementations16 Aug 2019 Xun Xu, Loong-Fah Cheong, Zhuwen Li

Many real-world video sequences cannot be conveniently categorized as general or degenerate; in such cases, imposing a false dichotomy in using the fundamental matrix or homography model for motion segmentation on video sequences would lead to difficulty.

Model Selection Motion Segmentation

Zero-Shot Crowd Behavior Recognition

no code implementations16 Aug 2019 Xun Xu, Shaogang Gong, Timothy Hospedales

To that end, we relax the common assumption that each individual crowd video instance is only associated with a single crowd attribute.

Zero-Shot Learning

C3AE: Exploring the Limits of Compact Model for Age Estimation

1 code implementation CVPR 2019 Chao Zhang, Shuaicheng Liu, Xun Xu, Ce Zhu

Recently, MobileNets and ShuffleNets have been proposed to reduce the number of parameters, yielding lightweight models.

Age Estimation

Learning for Multi-Type Subspace Clustering

1 code implementation3 Apr 2019 Xun Xu, Loong-Fah Cheong, Zhuwen Li

Subspace clustering has been extensively studied from the hypothesis-and-test, algebraic, and spectral clustering based perspectives.

Robust Video Background Identification by Dominant Rigid Motion Estimation

no code implementations6 Mar 2019 Kaimo Lin, Nianjuan Jiang, Loong Fah Cheong, Jiangbo Lu, Xun Xu

In this paper, we propose an efficient local-to-global method to identify background, based on the assumption that as long as there is sufficient camera motion, the cumulative background features will have the largest amount of trajectories.

Motion Estimation Motion Segmentation +1

Learning for Multi-Model and Multi-Type Fitting

no code implementations29 Jan 2019 Xun Xu, Loong-Fah Cheong, Zhuwen Li

Multi-model fitting has been extensively studied from the random sampling and clustering perspectives.

Model Selection

Image Ordinal Classification and Understanding: Grid Dropout with Masking Label

no code implementations8 May 2018 Chao Zhang, Ce Zhu, Jimin Xiao, Xun Xu, Yipeng Liu

Finally we demonstrate the effectiveness of both approaches by visualizing the Class Activation Map (CAM) and discover that grid dropout is more aware of the whole facial areas and more robust than neuron dropout for small training dataset.

Age Estimation Classification +2

Motion Segmentation by Exploiting Complementary Geometric Models

1 code implementation CVPR 2018 Xun Xu, Loong-Fah Cheong, Zhuwen Li

Many real-world sequences cannot be conveniently categorized as general or degenerate; in such cases, imposing a false dichotomy in using the fundamental matrix or homography model for motion segmentation would lead to difficulty.

Motion Segmentation

Multi-Task Zero-Shot Action Recognition with Prioritised Data Augmentation

no code implementations26 Nov 2016 Xun Xu, Timothy M. Hospedales, Shaogang Gong

In this work, we improve the ability of ZSL to generalise across this domain shift in both model- and data-centric ways by formulating a visual-semantic mapping with better generalisation properties and a dynamic data re-weighting method to prioritise auxiliary data that are relevant to the target classes.

Action Recognition Data Augmentation +1

Latent Model Ensemble with Auto-localization

no code implementations15 Apr 2016 Miao Sun, Tony X. Han, Xun Xu, Ming-Chang Liu, Ahmad Khodayari-Rostamabad

Deep Convolutional Neural Networks (CNN) have exhibited superior performance in many visual recognition tasks including image classification, object detection, and scene label- ing, due to their large learning capacity and resistance to overfit.

Classification General Classification +3

Transductive Zero-Shot Action Recognition by Word-Vector Embedding

no code implementations13 Nov 2015 Xun Xu, Timothy Hospedales, Shaogang Gong

This is a more challenging problem than existing ZSL of still images and/or attributes, because the mapping between video spacetime features of actions and the semantic space is more complex and harder to learn for the purpose of generalising over any cross-category domain shift.

Action Recognition Zero-Shot Action Recognition

Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization

no code implementations27 Jul 2015 Xun Xu, Timothy Hospedales, Shaogang Gong

The growing rate of public space CCTV installations has generated a need for automated methods for exploiting video surveillance data including scene understanding, query, behaviour annotation and summarization.

Scene Understanding Semantic Similarity +2

Semantic Embedding Space for Zero-Shot Action Recognition

no code implementations5 Feb 2015 Xun Xu, Timothy Hospedales, Shaogang Gong

In this framework a mapping is constructed between visual features and a human interpretable semantic description of each category, allowing categories to be recognised in the absence of any training data.

Action Recognition Data Augmentation +1

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