Search Results for author: Zhang Zhang

Found 26 papers, 11 papers with code

Semantic Prompt for Few-Shot Image Recognition

no code implementations24 Mar 2023 Wentao Chen, Chenyang Si, Zhang Zhang, Liang Wang, Zilei Wang, Tieniu Tan

Instead of the naive exploitation of semantic information for remedying classifiers, we explore leveraging semantic information as prompts to tune the visual feature extraction network adaptively.

Few-Shot Learning

Human Image Generation: A Comprehensive Survey

no code implementations17 Dec 2022 Zhen Jia, Zhang Zhang, Liang Wang, Tieniu Tan

Image and video synthesis has become a blooming topic in computer vision and machine learning communities along with the developments of deep generative models, due to its great academic and application value.

Data Augmentation Image Generation +2

Domain-Specific Risk Minimization for Out-of-Distribution Generalization

no code implementations18 Aug 2022 Yi-Fan Zhang, Jindong Wang, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, DaCheng Tao, Xing Xie

Our bound motivates two strategies to reduce the gap: the first one is ensembling multiple classifiers to enrich the hypothesis space, then we propose effective gap estimation methods for guiding the selection of a better hypothesis for the target.

Domain Generalization Out-of-Distribution Generalization

Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations

1 code implementation16 Jul 2022 Wentao Chen, Zhang Zhang, Wei Wang, Liang Wang, Zilei Wang, Tieniu Tan

Different from previous cross-domain FSL work (CD-FSL) that considers the domain shift between base and novel classes, the new problem, termed cross-domain cross-set FSL (CDSC-FSL), requires few-shot learners not only to adapt to the new domain, but also to be consistent between different domains within each novel class.

Few-Shot Learning

Completing Networks by Learning Local Connection Patterns

1 code implementation25 Apr 2022 Zhang Zhang, Ruyi Tao, Yongzai Tao, Mingze Qi, Jiang Zhang

And experiments show that our model perform better on a network with higher Reachable CC.

Link Prediction

Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data

1 code implementation30 Dec 2021 Shenwang Jiang, Jianan Li, Ying Wang, Bo Huang, Zhang Zhang, Tingfa Xu

In practice, however, biased samples with corrupted labels and of tailed classes commonly co-exist in training data.


Intention Recognition for Multiple Agents

no code implementations5 Dec 2021 Zhang Zhang, Yifeng Zeng, Yinghui Pan

Then, we transform the intention recognition into an un-supervised learning problem and adapt a clustering algorithm to group intentions of multiple agents through comparing their behavioural models.

Intent Detection

Generalizable Person Re-identification Without Demographics

no code implementations29 Sep 2021 Yifan Zhang, Feng Li, Zhang Zhang, Liang Wang, DaCheng Tao, Tieniu Tan

However, the convex condition of KL DRO may not hold for overparameterized neural networks, such that applying KL DRO often fails to generalize under distribution shifts in real scenarios.

Generalizable Person Re-identification

Focal and Efficient IOU Loss for Accurate Bounding Box Regression

no code implementations20 Jan 2021 Yi-Fan Zhang, Weiqiang Ren, Zhang Zhang, Zhen Jia, Liang Wang, Tieniu Tan

(ii) Most of the loss functions ignore the imbalance problem in BBR that the large number of anchor boxes which have small overlaps with the target boxes contribute most to the optimization of BBR.

object-detection Object Detection +2

Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition

1 code implementation20 Oct 2020 Yi-Fan Song, Zhang Zhang, Caifeng Shan, Liang Wang

However, the complexity of the State-Of-The-Art (SOTA) models of this task tends to be exceedingly sophisticated and over-parameterized, where the low efficiency in model training and inference has obstructed the development in the field, especially for large-scale action datasets.

Action Recognition Skeleton Based Action Recognition

Richly Activated Graph Convolutional Network for Robust Skeleton-based Action Recognition

3 code implementations9 Aug 2020 Yi-Fan Song, Zhang Zhang, Caifeng Shan, Liang Wang

More crucially, on the synthetic occlusion and jittering datasets, the performance deterioration due to the occluded and disturbed joints can be significantly alleviated by utilizing the proposed RA-GCN.

Action Recognition Skeleton Based Action Recognition +1

Slow Feature Analysis for Human Action Recognition

no code implementations15 Jul 2019 Zhang Zhang, DaCheng Tao

In this paper, we introduce the SFA framework to the problem of human action recognition by incorporating the discriminative information with SFA learning and considering the spatial relationship of body parts.

Action Recognition Temporal Action Localization

Richly Activated Graph Convolutional Network for Action Recognition with Incomplete Skeletons

3 code implementations16 May 2019 Yi-Fan Song, Zhang Zhang, Liang Wang

To enhance the robustness of action recognition models to incomplete skeletons, we propose a multi-stream graph convolutional network (GCN) for exploring sufficient discriminative features distributed over all skeleton joints.

Action Recognition Skeleton Based Action Recognition +1

Large-Scale Pedestrian Retrieval Competition

no code implementations6 Mar 2019 Da Li, Zhang Zhang

The Large-Scale Pedestrian Retrieval Competition (LSPRC) mainly focuses on person retrieval which is an important end application in intelligent vision system of surveillance.

Pedestrian Detection Person Retrieval +1

A General Deep Learning Framework for Network Reconstruction and Dynamics Learning

1 code implementation30 Dec 2018 Zhang Zhang, Yi Zhao, Jing Liu, Shuo Wang, Ruyi Tao, Ruyue Xin, Jiang Zhang

We exhibit the universality of our framework on different kinds of time-series data: with the same structure, our model can be trained to accurately recover the network structure and predict future states on continuous, discrete, and binary dynamics, and outperforms competing network reconstruction methods.

Time Series Analysis

The Cinderella Complex: Word Embeddings Reveal ender Stereotypes in Movies and Books

1 code implementation12 Nov 2018 Huimin Xu, Zhang Zhang, Lingfei Wu, Cheng-Jun Wang

Our analysis of thousands of movies and books reveals how these cultural products weave stereotypical gender roles into morality tales and perpetuate gender inequality through storytelling.

Word Embeddings

Learning Deep Context-aware Features over Body and Latent Parts for Person Re-identification

no code implementations CVPR 2017 Dangwei Li, Xiaotang Chen, Zhang Zhang, Kaiqi Huang

It is a challenging task due to the large variations in person pose, occlusion, background clutter, etc How to extract powerful features is a fundamental problem in ReID and is still an open problem today.

Person Identification Person Re-Identification +1

A Large-scale Distributed Video Parsing and Evaluation Platform

no code implementations29 Nov 2016 Kai Yu, Yang Zhou, Da Li, Zhang Zhang, Kaiqi Huang

Visual surveillance systems have become one of the largest data sources of Big Visual Data in real world.

Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization

no code implementations17 Nov 2016 Kai Yu, Biao Leng, Zhang Zhang, Dangwei Li, Kaiqi Huang

Based on GoogLeNet, firstly, a set of mid-level attribute features are discovered by novelly designed detection layers, where a max-pooling based weakly-supervised object detection technique is used to train these layers with only image-level labels without the need of bounding box annotations of pedestrian attributes.

Multi-Label Image Classification object-detection +3

ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering

no code implementations CVPR 2016 Zhang Zhang, Kaiqi Huang, Tieniu Tan, Peipei Yang, Jun Li

For spectral embedding/clustering, it is still an open problem on how to construct an relation graph to reflect the intrinsic structures in data.

graph construction Motion Segmentation +2

A Richly Annotated Dataset for Pedestrian Attribute Recognition

2 code implementations23 Mar 2016 Dangwei Li, Zhang Zhang, Xiaotang Chen, Haibin Ling, Kaiqi Huang

RAP has in total 41, 585 pedestrian samples, each of which is annotated with 72 attributes as well as viewpoints, occlusions, body parts information.

Pedestrian Attribute Recognition

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