Search Results for author: Shiming Chen

Found 17 papers, 7 papers with code

Progressive Semantic-Guided Vision Transformer for Zero-Shot Learning

no code implementations11 Apr 2024 Shiming Chen, Wenjin Hou, Salman Khan, Fahad Shahbaz Khan

ZSLViT mainly considers two properties in the whole network: i) discover the semantic-related visual representations explicitly, and ii) discard the semantic-unrelated visual information.

Zero-Shot Learning

Few-Shot Object Detection: Research Advances and Challenges

no code implementations7 Apr 2024 Zhimeng Xin, Shiming Chen, Tianxu Wu, Yuanjie Shao, Weiping Ding, Xinge You

This paper presents a comprehensive survey to review the significant advancements in the field of FSOD in recent years and summarize the existing challenges and solutions.

Few-Shot Learning Few-Shot Object Detection +2

HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization

no code implementations18 Jan 2024 Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang

Domain Generalization (DG) endeavors to create machine learning models that excel in unseen scenarios by learning invariant features.

Contrastive Learning Domain Generalization

ECEA: Extensible Co-Existing Attention for Few-Shot Object Detection

no code implementations15 Sep 2023 Zhimeng Xin, Tianxu Wu, Shiming Chen, Yixiong Zou, Ling Shao, Xinge You

Extensive experiments on the PASCAL VOC and COCO datasets show that our ECEA module can assist the few-shot detector to completely predict the object despite some regions failing to appear in the training samples and achieve the new state of the art compared with existing FSOD methods.

Few-Shot Object Detection Object +1

EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning

no code implementations19 Aug 2023 Shiming Chen, Shihuang Chen, Wenjin Hou, Weiping Ding, Xinge You

However, existing GAN-based generative ZSL methods are based on hand-crafted models, which cannot adapt to various datasets/scenarios and fails to model instability.

Generative Adversarial Network Neural Architecture Search +1

Evolving Semantic Prototype Improves Generative Zero-Shot Learning

no code implementations12 Jun 2023 Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang

After alignment, synthesized sample features from unseen classes are closer to the real sample features and benefit DSP to improve existing generative ZSL methods by 8. 5\%, 8. 0\%, and 9. 7\% on the standard CUB, SUN AWA2 datasets, the significant performance improvement indicates that evolving semantic prototype explores a virgin field in ZSL.

Zero-Shot Learning

Emerging Synergies in Causality and Deep Generative Models: A Survey

no code implementations29 Jan 2023 Guanglin Zhou, Shaoan Xie, GuangYuan Hao, Shiming Chen, Biwei Huang, Xiwei Xu, Chen Wang, Liming Zhu, Lina Yao, Kun Zhang

In the field of artificial intelligence (AI), the quest to understand and model data-generating processes (DGPs) is of paramount importance.

Causal Identification Fairness +1

Both Diverse and Realism Matter: Physical Attribute and Style Alignment for Rainy Image Generation

no code implementations ICCV 2023 Changfeng Yu, Shiming Chen, Yi Chang, Yibing Song, Luxin Yan

To solve this dilemma, we propose a physical alignment and controllable generation network (PCGNet) for diverse and realistic rain generation.

Attribute Image Generation +1

MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning

2 code implementations CVPR 2022 Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You

Prior works either simply align the global features of an image with its associated class semantic vector or utilize unidirectional attention to learn the limited latent semantic representations, which could not effectively discover the intrinsic semantic knowledge e. g., attribute semantics) between visual and attribute features.

Attribute Transfer Learning +1

TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning

1 code implementation16 Dec 2021 Shiming Chen, Ziming Hong, Wenjin Hou, Guo-Sen Xie, Yibing Song, Jian Zhao, Xinge You, Shuicheng Yan, Ling Shao

Analogously, VAT uses the similar feature augmentation encoder to refine the visual features, which are further applied in visual$\rightarrow$attribute decoder to learn visual-based attribute features.

Attribute Zero-Shot Learning

TransZero: Attribute-guided Transformer for Zero-Shot Learning

1 code implementation3 Dec 2021 Shiming Chen, Ziming Hong, Yang Liu, Guo-Sen Xie, Baigui Sun, Hao Li, Qinmu Peng, Ke Lu, Xinge You

Although some attention-based models have attempted to learn such region features in a single image, the transferability and discriminative attribute localization of visual features are typically neglected.

Attribute Zero-Shot Learning

HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning

2 code implementations NeurIPS 2021 Shiming Chen, Guo-Sen Xie, Yang Liu, Qinmu Peng, Baigui Sun, Hao Li, Xinge You, Ling Shao

Specifically, HSVA aligns the semantic and visual domains by adopting a hierarchical two-step adaptation, i. e., structure adaptation and distribution adaptation.

Transfer Learning Zero-Shot Learning

FREE: Feature Refinement for Generalized Zero-Shot Learning

1 code implementation ICCV 2021 Shiming Chen, Wenjie Wang, Beihao Xia, Qinmu Peng, Xinge You, Feng Zheng, Ling Shao

FREE employs a feature refinement (FR) module that incorporates \textit{semantic$\rightarrow$visual} mapping into a unified generative model to refine the visual features of seen and unseen class samples.

Generalized Zero-Shot Learning

BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction

no code implementations8 Oct 2020 Beihao Xia, Conghao Wong, Heng Li, Shiming Chen, Qinmu Peng, Xinge You

Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors.

Trajectory Prediction

CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network

1 code implementation21 Aug 2020 Shiming Chen, Wenjie Wang, Beihao Xia, Xinge You, Zehong Cao, Weiping Ding

In essence, CDE-GAN incorporates dual evolution with respect to the generator(s) and discriminators into a unified evolutionary adversarial framework to conduct effective adversarial multi-objective optimization.

GAN image forensics Generative Adversarial Network +1

Kernelized Similarity Learning and Embedding for Dynamic Texture Synthesis

1 code implementation11 Nov 2019 Shiming Chen, Peng Zhang, Guo-Sen Xie, Qinmu Peng, Zehong Cao, Wei Yuan, Xinge You

Dynamic texture (DT) exhibits statistical stationarity in the spatial domain and stochastic repetitiveness in the temporal dimension, indicating that different frames of DT possess a high similarity correlation that is critical prior knowledge.

Texture Synthesis

Semi-supervised Feature Learning For Improving Writer Identification

no code implementations15 Jul 2018 Shiming Chen, Yisong Wang, Chin-Teng Lin, Weiping Ding, Zehong Cao

In this study, a semi-supervised feature learning pipeline was proposed to improve the performance of writer identification by training with extra unlabeled data and the original labeled data simultaneously.

Data Augmentation

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