Search Results for author: Liansheng Zhuang

Found 12 papers, 3 papers with code

Hierarchical Prompts for Rehearsal-free Continual Learning

no code implementations21 Jan 2024 Yukun Zuo, Hantao Yao, Lu Yu, Liansheng Zhuang, Changsheng Xu

Nonetheless, these learnable prompts tend to concentrate on the discriminatory knowledge of the current task while ignoring past task knowledge, leading to that learnable prompts still suffering from catastrophic forgetting.

Continual Learning

Hierarchical Augmentation and Distillation for Class Incremental Audio-Visual Video Recognition

1 code implementation11 Jan 2024 Yukun Zuo, Hantao Yao, Liansheng Zhuang, Changsheng Xu

We introduce Hierarchical Augmentation and Distillation (HAD), which comprises the Hierarchical Augmentation Module (HAM) and Hierarchical Distillation Module (HDM) to efficiently utilize the hierarchical structure of data and models, respectively.

Video Recognition

Learning Differentially Private Probabilistic Models for Privacy-Preserving Image Generation

no code implementations18 May 2023 Bochao Liu, Shiming Ge, Pengju Wang, Liansheng Zhuang, Tongliang Liu

In particular, we first train a model to fit the distribution of the training data and make it satisfy differential privacy by performing a randomized response mechanism during training process.

Image Generation Privacy Preserving

LayoutDM: Transformer-based Diffusion Model for Layout Generation

no code implementations CVPR 2023 Shang Chai, Liansheng Zhuang, Fengying Yan

Though existing methods based on generative models such as Generative Adversarial Networks (GANs) and Variational Auto-Encoders (VAEs) have progressed, they still leave much room for improving the quality and diversity of the results.


Estimation of Reliable Proposal Quality for Temporal Action Detection

1 code implementation25 Apr 2022 Junshan Hu, Chaoxu Guo, Liansheng Zhuang, Biao Wang, Tiezheng Ge, Yuning Jiang, Houqiang Li

For the region perspective, we introduce Region Evaluate Module (REM) which uses a new and efficient sampling method for proposal feature representation containing more contextual information compared with point feature to refine category score and proposal boundary.

Action Detection

One-shot Key Information Extraction from Document with Deep Partial Graph Matching

no code implementations26 Sep 2021 Minghong Yao, Zhiguang Liu, Liangwei Wang, Houqiang Li, Liansheng Zhuang

However, collecting and labeling a large dataset is time-consuming and is not a user-friendly requirement for many cloud platforms.

Graph Matching Key Information Extraction

Soft Hindsight Experience Replay

2 code implementations6 Feb 2020 Qiwei He, Liansheng Zhuang, Houqiang Li

However, due to the brittleness of deterministic methods, HER and its variants typically suffer from a major challenge for stability and convergence, which significantly affects the final performance.

reinforcement-learning Reinforcement Learning (RL)

Graph Construction with Label Information for Semi-Supervised Learning

no code implementations8 Jul 2016 Liansheng Zhuang, Zihan Zhou, Jingwen Yin, Shenghua Gao, Zhouchen Lin, Yi Ma, Nenghai Yu

In the literature, most existing graph-based semi-supervised learning (SSL) methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph.

graph construction Graph Learning

Constructing a Non-Negative Low Rank and Sparse Graph with Data-Adaptive Features

no code implementations3 Sep 2014 Liansheng Zhuang, Shenghua Gao, Jinhui Tang, Jingjing Wang, Zhouchen Lin, Yi Ma

This paper aims at constructing a good graph for discovering intrinsic data structures in a semi-supervised learning setting.

graph construction

Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment

no code implementations8 Feb 2014 Liansheng Zhuang, Tsung-Han Chan, Allen Y. Yang, S. Shankar Sastry, Yi Ma

In particular, the single-sample face alignment accuracy is comparable to that of the well-known Deformable SRC algorithm using multiple gallery images per class.

Face Alignment Face Recognition +1

Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer

no code implementations CVPR 2013 Liansheng Zhuang, Allen Y. Yang, Zihan Zhou, S. Shankar Sastry, Yi Ma

To compensate the missing illumination information typically provided by multiple training images, a sparse illumination transfer (SIT) technique is introduced.

Face Alignment Face Recognition +1

Cannot find the paper you are looking for? You can Submit a new open access paper.