1 code implementation • NeurIPS 2023 • Weijia Wu, Yuzhong Zhao, Hao Chen, YuChao Gu, Rui Zhao, Yefei He, Hong Zhou, Mike Zheng Shou, Chunhua Shen
To showcase the power of the proposed approach, we generate datasets with rich dense pixel-wise labels for a wide range of downstream tasks, including semantic segmentation, instance segmentation, and depth estimation.
1 code implementation • 20 Mar 2022 • Weijia Wu, Yuanqiang Cai, Chunhua Shen, Debing Zhang, Ying Fu, Hong Zhou, Ping Luo
Recent video text spotting methods usually require the three-staged pipeline, i. e., detecting text in individual images, recognizing localized text, tracking text streams with post-processing to generate final results.
3 code implementations • 9 Dec 2021 • Weijia Wu, Yuanqiang Cai, Debing Zhang, Sibo Wang, Zhuang Li, Jiahong Li, Yejun Tang, Hong Zhou
Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data.
1 code implementation • 26 Nov 2020 • Weijia Wu, Enze Xie, Ruimao Zhang, Wenhai Wang, Hong Zhou, Ping Luo
For example, without using polygon annotations, PSENet achieves an 80. 5% F-score on TotalText [3] (vs. 80. 9% of fully supervised counterpart), 31. 1% better than training directly with upright bounding box annotations, and saves 80%+ labeling costs.
1 code implementation • 5 Oct 2023 • Yefei He, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
In this paper, we introduce a data-free and parameter-efficient fine-tuning framework for low-bit diffusion models, dubbed EfficientDM, to achieve QAT-level performance with PTQ-like efficiency.
1 code implementation • 25 Dec 2017 • Jiachi Zhang, Xiaolei Shen, Tianqi Zhuo, Hong Zhou
Since the proposal of fully convolutional neural network (FCNN), it has been widely used in semantic segmentation because of its high accuracy of pixel-wise classification as well as high precision of localization.
1 code implementation • 5 May 2023 • Weijia Wu, Yuzhong Zhao, Zhuang Li, Jiahong Li, Hong Zhou, Mike Zheng Shou, Xiang Bai
Most existing cross-modal language-to-video retrieval (VR) research focuses on single-modal input from video, i. e., visual representation, while the text is omnipresent in human environments and frequently critical to understand video.
1 code implementation • 29 Nov 2023 • Weijia Wu, Yuzhong Zhao, Zhuang Li, Lianlei Shan, Hong Zhou, Mike Zheng Shou
Image segmentation based on continual learning exhibits a critical drop of performance, mainly due to catastrophic forgetting and background shift, as they are required to incorporate new classes continually.
1 code implementation • ICCV 2023 • Weijia Wu, Yuzhong Zhao, Mike Zheng Shou, Hong Zhou, Chunhua Shen
In contrast, synthetic data can be freely available using a generative model (e. g., DALL-E, Stable Diffusion).
1 code implementation • 27 Jun 2023 • Junyi Bian, Rongze Jiang, Weiqi Zhai, Tianyang Huang, Hong Zhou, Shanfeng Zhu
Biomedical named entity recognition (BNER) serves as the foundation for numerous biomedical text mining tasks.
1 code implementation • 30 Dec 2021 • Zhuang Li, Weijia Wu, Mike Zheng Shou, Jiahong Li, Size Li, Zhongyuan Wang, Hong Zhou
Semantic representation is of great benefit to the video text tracking(VTT) task that requires simultaneously classifying, detecting, and tracking texts in the video.
1 code implementation • 18 Jul 2022 • Wejia Wu, Zhuang Li, Jiahong Li, Chunhua Shen, Hong Zhou, Size Li, Zhongyuan Wang, Ping Luo
Our contributions are three-fold: 1) CoText simultaneously address the three tasks (e. g., text detection, tracking, recognition) in a real-time end-to-end trainable framework.
1 code implementation • 18 Nov 2022 • Junyi Bian, Xiaodi Huang, Hong Zhou, Shanfeng Zhu
In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization.
Ranked #4 on Text Summarization on Pubmed
1 code implementation • 25 Feb 2024 • Luoming Zhang, Yefei He, Wen Fei, Zhenyu Lou, Weijia Wu, YangWei Ying, Hong Zhou
Our framework outperforms previous methods by approximately 1\% for 8-bit PTQ and 2\% for 6-bit PTQ, showcasing its superior performance.
no code implementations • 13 Nov 2017 • Xiaolei Shen, Jiachi Zhang, Chenjun Yan, Hong Zhou
The core of our method is to extract features of images based on convolutional neural network and achieve classification by classifier.
no code implementations • 22 Apr 2019 • Weijia Wu, Jici Xing, Hong Zhou
In this paper, we propose a pixel-wise method named TextCohesion for scene text detection, which splits a text instance into five key components: a Text Skeleton and four Directional Pixel Regions.
Ranked #1 on Curved Text Detection on SCUT-CTW1500
no code implementations • 29 Oct 2020 • Lap Chi Lau, Hong Zhou
We present a local search framework to design and analyze both combinatorial algorithms and rounding algorithms for experimental design problems.
no code implementations • ICCV 2021 • Jinlei Hou, Yingying Zhang, Qiaoyong Zhong, Di Xie, ShiLiang Pu, Hong Zhou
Surprisingly, by varying the granularity of division on feature maps, we are able to modulate the reconstruction capability of the model for both normal and abnormal samples.
no code implementations • 11 Jan 2022 • Wei Kang, Liang Xu, Hong Zhou
In this paper, we introduce the concept of observability of targeted state variables for systems that may not be fully observable.
no code implementations • 8 Apr 2022 • Yefei He, Luoming Zhang, Weijia Wu, Hong Zhou
In this paper, we present a simple yet effective data-free quantization method with accurate activation clipping and adaptive batch normalization.
no code implementations • 16 May 2022 • Yefei He, Luoming Zhang, Weijia Wu, Hong Zhou
Extensive experiments demonstrate that the proposed method yields surprising performance both in image classification and human pose estimation tasks.
Ranked #1 on Binarization on ImageNet (Top 1 Accuracy metric)
no code implementations • 14 Nov 2022 • Yefei He, Zhenyu Lou, Luoming Zhang, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
To solve this, we propose Softmax-aware Binarization, which dynamically adapts to the data distribution and reduces the error caused by binarization.
no code implementations • 3 May 2023 • Lap Chi Lau, Robert Wang, Hong Zhou
We prove that a randomized local search approach provides a unified algorithm to solve this problem for all $p$.
no code implementations • 14 Jul 2023 • Wei Kang, Liang Xu, Hong Zhou
We propose a novel learning-based surrogate data assimilation (DA) model for efficient state estimation in a limited area.
no code implementations • ICCV 2023 • Yefei He, Zhenyu Lou, Luoming Zhang, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
To solve this, we propose Softmax-aware Binarization, which dynamically adapts to the data distribution and reduces the error caused by binarization.
no code implementations • 7 Oct 2023 • Luoming Zhang, Wen Fei, Weijia Wu, Yefei He, Zhenyu Lou, Hong Zhou
Fine-grained quantization has smaller quantization loss, consequently achieving superior performance.
no code implementations • 9 Nov 2023 • Cheng Yang, Rui Xu, Ye Guo, Peixiang Huang, Yiru Chen, Wenkui Ding, Zhongyuan Wang, Hong Zhou
Further, we design two pre-training tasks named object position regression (OPR) and spatial relation classification (SRC) to learn to reconstruct the spatial relation graph respectively.
no code implementations • 23 Jan 2024 • Hong Zhou, Rui Zhang, Peifeng Lai, Chaoran Guo, Yong Wang, Zhida Sun, Junjie Li
Therefore, a visualization system is needed to assist ViT users in understanding its functionality.
no code implementations • 29 Feb 2024 • Jianfeng Chen, Jize Xiong, Yixu Wang, Qi Xin, Hong Zhou
With the application of hematopoietic stem cell transplantation and new drugs, the progression-free survival rate and overall survival rate of multiple myeloma have been greatly improved, but it is still considered as a kind of disease that cannot be completely cured.
no code implementations • 14 Apr 2024 • Yufu Wang, Mingwei Zhu, Jiaqiang Yuan, Guanghui Wang, Hong Zhou
Cloud computing (cloud computing) is a kind of distributed computing, referring to the network "cloud" will be a huge data calculation and processing program into countless small programs, and then, through the system composed of multiple servers to process and analyze these small programs to get the results and return to the user.