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.
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.
no code implementations • 28 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.
no code implementations • 27 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.
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.
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.
1 code implementation • 12 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.
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.
1 code implementation • CVPR 2021 • Spencer Whitehead, Hui Wu, Heng Ji, Rogerio Feris, Kate Saenko
Generalization to out-of-distribution data has been a problem for Visual Question Answering (VQA) models.
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.
1 code implementation • 26 Nov 2020 • Spencer Whitehead, Hui Wu, Yi Ren Fung, Heng Ji, Rogerio Feris, Kate Saenko
Existing Visual Question Answering (VQA) models are often fragile and sensitive to input variations.
no code implementations • 20 Nov 2020 • Ulrich Finkler, Michele Merler, Rameswar Panda, Mayoore S. Jaiswal, Hui Wu, Kandan Ramakrishnan, Chun-Fu Chen, Minsik Cho, David Kung, Rogerio Feris, Bishwaranjan Bhattacharjee
Neural Architecture Search (NAS) is a powerful tool to automatically design deep neural networks for many tasks, including image classification.
no code implementations • 23 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.
no code implementations • 6 Mar 2020 • Kaichen Zhou, Shiji Song, Anke Xue, Keyou You, Hui Wu
Then we develop two algorithms for optimizing the energy efficiency of train operation.
no code implementations • 27 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.
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.
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.
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.
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.
1 code implementation • 9 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 .
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.
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.