Search Results for author: Ruiying Lu

Found 13 papers, 9 papers with code

BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging

1 code implementation ECCV 2020 Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen, Ziyi Meng, Xin Yuan

This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames.

Latent Diffusion Prior Enhanced Deep Unfolding for Spectral Image Reconstruction

no code implementations24 Nov 2023 Zongliang Wu, Ruiying Lu, Ying Fu, Xin Yuan

Snapshot compressive spectral imaging reconstruction aims to reconstruct three-dimensional spatial-spectral images from a single-shot two-dimensional compressed measurement.

Computational Efficiency Image Reconstruction +1

Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection

1 code implementation NeurIPS 2023 Ruiying Lu, Yujie Wu, Long Tian, Dongsheng Wang, Bo Chen, Xiyang Liu, Ruimin Hu

First, instead of learning the continuous representations, we preserve the typical normal patterns as discrete iconic prototypes, and confirm the importance of Vector Quantization in preventing the model from falling into the shortcut.

Quantization Unsupervised Anomaly Detection

PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image Classification

1 code implementation ICCV 2023 Miaoge Li, Dongsheng Wang, Xinyang Liu, Zequn Zeng, Ruiying Lu, Bo Chen, Mingyuan Zhou

We find that by formulating the multi-label classification as a CT problem, we can exploit the interactions between the image and label efficiently by minimizing the bidirectional CT cost.

Multi-Label Classification Multi-Label Image Classification

ConZIC: Controllable Zero-shot Image Captioning by Sampling-Based Polishing

1 code implementation CVPR 2023 Zequn Zeng, Hao Zhang, Zhengjue Wang, Ruiying Lu, Dongsheng Wang, Bo Chen

Zero-shot capability has been considered as a new revolution of deep learning, letting machines work on tasks without curated training data.

Image Captioning Language Modelling

HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding

1 code implementation16 Oct 2022 Yishi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou

With the tree-likeness property of hyperbolic space, the underlying semantic hierarchy among words and topics can be better exploited to mine more interpretable topics.

Graph structure learning Topic Models

Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing

no code implementations1 Mar 2022 Ruiying Lu, Ziheng Cheng, Bo Chen, Xin Yuan

Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compresses them into a single measurement.

Compressive Sensing Video Compressive Sensing

Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural Network

1 code implementation11 Sep 2021 Ruiying Lu, Bo Chen, Guanliang Liu, Ziheng Cheng, Mu Qiao, Xin Yuan

In this paper, we propose an optical flow-aided recurrent neural network for dual video SCI systems, which provides high-quality decoding in seconds.

Compressive Sensing Optical Flow Estimation

Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning

1 code implementation10 May 2021 Dandan Guo, Ruiying Lu, Bo Chen, Zequn Zeng, Mingyuan Zhou

Inspired by recent successes in integrating semantic topics into this task, this paper develops a plug-and-play hierarchical-topic-guided image paragraph generation framework, which couples a visual extractor with a deep topic model to guide the learning of a language model.

Image Paragraph Captioning Language Modelling +1

Memory-Efficient Network for Large-scale Video Compressive Sensing

2 code implementations CVPR 2021 Ziheng Cheng, Bo Chen, Guanliang Liu, Hao Zhang, Ruiying Lu, Zhengjue Wang, Xin Yuan

With the knowledge of masks, optimization algorithms or deep learning methods are employed to reconstruct the desired high-speed video frames from this snapshot measurement.

Compressive Sensing Demosaicking +1

Topic-aware Contextualized Transformers

no code implementations1 Jan 2021 Ruiying Lu, Bo Chen, Dan dan Guo, Dongsheng Wang, Mingyuan Zhou

Moving beyond conventional Transformers that ignore longer-range word dependencies and contextualize their word representations at the segment level, the proposed method not only captures global semantic coherence of all segments and global word concurrence patterns, but also enriches the representation of each token by adapting it to its local context, which is not limited to the segment it resides in and can be flexibly defined according to the task.

Word Embeddings

Recurrent Hierarchical Topic-Guided RNN for Language Generation

1 code implementation ICML 2020 Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou

To simultaneously capture syntax and global semantics from a text corpus, we propose a new larger-context recurrent neural network (RNN) based language model, which extracts recurrent hierarchical semantic structure via a dynamic deep topic model to guide natural language generation.

Language Modelling Sentence +1

Recurrent Hierarchical Topic-Guided Neural Language Models

no code implementations25 Sep 2019 Dandan Guo, Bo Chen, Ruiying Lu, Mingyuan Zhou

To simultaneously capture syntax and semantics from a text corpus, we propose a new larger-context language model that extracts recurrent hierarchical semantic structure via a dynamic deep topic model to guide natural language generation.

Language Modelling Sentence +1

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