Search Results for author: Hui Wu

Found 22 papers, 11 papers with code

Synchronous Dual Network with Cross-Type Attention for Joint Entity and Relation Extraction

no code implementations EMNLP 2021 Hui Wu, Xiaodong Shi

In this paper, we design a novel synchronous dual network (SDN) with cross-type attention via separately and interactively considering the entity types and relation types.

Joint Entity and Relation Extraction Multi-Task Learning +3

Adversarial Soft Prompt Tuning for Cross-Domain Sentiment Analysis

no code implementations ACL 2022 Hui Wu, Xiaodong Shi

On the other hand, AdSPT uses a novel domain adversarial training strategy to learn domain-invariant representations between each source domain and the target domain.

Domain Adaptation Language Modelling +2

A 97 fJ/Conversion Neuron-ADC with Reconfigurable Sampling and Static Power Reduction

no code implementations28 Nov 2022 Jinbo Chen, Hui Wu, Jie Yang, Mohamad Sawan

A bio-inspired Neuron-ADC with reconfigurable sampling and static power reduction for biomedical applications is proposed in this work.

Recent Trends and Future Prospects of Neural Recording Circuits and Systems: A Tutorial Brief

no code implementations27 May 2022 Jinbo Chen, Mahdi Tarkhan, Hui Wu, Fereidoon Hashemi Noshahr, Jie Yang, Mohamad Sawan

Recent years have seen fast advances in neural recording circuits and systems as they offer a promising way to investigate real-time brain monitoring and the closed-loop modulation of psychological disorders and neurodegenerative diseases.

SimVQA: Exploring Simulated Environments for Visual Question Answering

no code implementations CVPR 2022 Paola Cascante-Bonilla, Hui Wu, Letao Wang, Rogerio Feris, Vicente Ordonez

By exploiting 3D and physics simulation platforms, we provide a pipeline to generate synthetic data to expand and replace type-specific questions and answers without risking the exposure of sensitive or personal data that might be present in real images.

Data Augmentation Question Answering +2

Contextual Similarity Distillation for Asymmetric Image Retrieval

no code implementations CVPR 2022 Hui Wu, Min Wang, Wengang Zhou, Houqiang Li, Qi Tian

To this end, we propose a flexible contextual similarity distillation framework to enhance the small query model and keep its output feature compatible with that of large gallery model, which is crucial with asymmetric retrieval.

Image Retrieval Retrieval

Learning Token-based Representation for Image Retrieval

1 code implementation12 Dec 2021 Hui Wu, Min Wang, Wengang Zhou, Yang Hu, Houqiang Li

Next, a refinement block is introduced to enhance the visual tokens with self-attention and cross-attention.

Image Retrieval Retrieval

Contextual Similarity Aggregation with Self-attention for Visual Re-ranking

1 code implementation NeurIPS 2021 Jianbo Ouyang, Hui Wu, Min Wang, Wengang Zhou, Houqiang Li

Since our re-ranking model is not directly involved with the visual feature used in the initial retrieval, it is ready to be applied to retrieval result lists obtained from various retrieval algorithms.

Content-Based Image Retrieval Data Augmentation +2

Learning Deep Local Features With Multiple Dynamic Attentions for Large-Scale Image Retrieval

1 code implementation ICCV 2021 Hui Wu, Min Wang, Wengang Zhou, Houqiang Li

To this end, we propose a novel deep local feature learning architecture to simultaneously focus on multiple discriminative local patterns in an image.

Image Retrieval Metric Learning +1

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search

no code implementations23 Jun 2020 Rameswar Panda, Michele Merler, Mayoore Jaiswal, Hui Wu, Kandan Ramakrishnan, Ulrich Finkler, Chun-Fu Chen, Minsik Cho, David Kung, Rogerio Feris, Bishwaranjan Bhattacharjee

The typical way of conducting large scale NAS is to search for an architectural building block on a small dataset (either using a proxy set from the large dataset or a completely different small scale dataset) and then transfer the block to a larger dataset.

Neural Architecture Search

A selected review on reinforcement learning based control for autonomous underwater vehicles

no code implementations27 Nov 2019 Ya-Chu Hsu, Hui Wu, Keyou You, Shiji Song

This paper provides a selected review on RL based control for AUVs with the focus on applications of RL to low-level control tasks for underwater regulation and tracking.


Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries

1 code implementation NeurIPS 2019 Fuwen Tan, Paola Cascante-Bonilla, Xiaoxiao Guo, Hui Wu, Song Feng, Vicente Ordonez

We show that using multiple rounds of natural language queries as input can be surprisingly effective to find arbitrarily specific images of complex scenes.

Image Retrieval Natural Language Queries +1

Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning

1 code implementation NeurIPS 2019 Wenjie Shi, Shiji Song, Hui Wu, Ya-Chu Hsu, Cheng Wu, Gao Huang

To tackle this problem, we propose a general acceleration method for model-free, off-policy deep RL algorithms by drawing the idea underlying regularized Anderson acceleration (RAA), which is an effective approach to accelerating the solving of fixed point problems with perturbations.

reinforcement-learning Reinforcement Learning (RL)

Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedback

2 code implementations CVPR 2021 Hui Wu, Yupeng Gao, Xiaoxiao Guo, Ziad Al-Halah, Steven Rennie, Kristen Grauman, Rogerio Feris

We provide a detailed analysis of the characteristics of the Fashion IQ data, and present a transformer-based user simulator and interactive image retriever that can seamlessly integrate visual attributes with image features, user feedback, and dialog history, leading to improved performance over the state of the art in dialog-based image retrieval.

Image Retrieval Retrieval

Dialog-based Interactive Image Retrieval

1 code implementation NeurIPS 2018 Xiaoxiao Guo, Hui Wu, Yu Cheng, Steven Rennie, Gerald Tesauro, Rogerio Schmidt Feris

Experiments on both simulated and real-world data show that 1) our proposed learning framework achieves better accuracy than other supervised and reinforcement learning baselines and 2) user feedback based on natural language rather than pre-specified attributes leads to more effective retrieval results, and a more natural and expressive communication interface.

Image Retrieval reinforcement-learning +3

A Systematic Analysis for State-of-the-Art 3D Lung Nodule Proposals Generation

1 code implementation9 Jan 2018 Hui Wu, Matrix Yao, Albert Hu, Gaofeng Sun, Xiaokun Yu, Jian Tang

Lung nodule proposals generation is the primary step of lung nodule detection and has received much attention in recent years .

Lung Nodule Detection

S3Pool: Pooling with Stochastic Spatial Sampling

4 code implementations CVPR 2017 Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogerio Feris

We view the pooling operation in CNNs as a two-step procedure: first, a pooling window (e. g., $2\times 2$) slides over the feature map with stride one which leaves the spatial resolution intact, and second, downsampling is performed by selecting one pixel from each non-overlapping pooling window in an often uniform and deterministic (e. g., top-left) manner.

Data Augmentation Image Classification

Robust Regression on Image Manifolds for Ordered Label Denoising

no code implementations CVPR 2015 Hui Wu, Richard Souvenir

In this paper, we present a computationally efficient and non-parametric method for robust regression on manifolds.

Denoising regression

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