1 code implementation • 26 Sep 2024 • Jian Li, Haojing Huang, Yujia Zhang, Pengfei Xu, Xi Chen, Rui Song, Lida Shi, Jingwen Wang, Hao Xu
Recently, there has been significant interest in replacing the reward model in Reinforcement Learning with Human Feedback (RLHF) methods for Large Language Models (LLMs), such as Direct Preference Optimization (DPO) and its variants.
no code implementations • 14 May 2024 • Jingwen Wang, Dehui Du, Yida Li, Yiyang Li, Yikang Chen
Several experiments demonstrate the feasibility of our approach in common environments, confirming its ability to enhance the effectiveness of DRL training and impart a certain level of explainability to the training process.
no code implementations • CVPR 2024 • Hengyi Wang, Jingwen Wang, Lourdes Agapito
Thanks to the expressiveness of neural representations prior works can accurately capture the motion and achieve high-fidelity reconstruction of the target object.
1 code implementation • 1 Dec 2023 • Hengyi Wang, Jingwen Wang, Lourdes Agapito
Thanks to the expressiveness of neural representations, prior works can accurately capture the motion and achieve high-fidelity reconstruction of the target object.
1 code implementation • 28 Jun 2023 • Jingwen Wang, Juan Tarrio, Lourdes Agapito, Pablo F. Alcantarilla, Alexander Vakhitov
We present a new methodology for real-time semantic mapping from RGB-D sequences that combines a 2D neural network and a 3D network based on a SLAM system with 3D occupancy mapping.
1 code implementation • 23 Jun 2023 • Tom Tongjia Chen, Hongshan Yu, Zhengeng Yang, Ming Li, Zechuan Li, Jingwen Wang, Wei Miao, Wei Sun, Chen Chen
Affordance-Centric Question-driven Task Completion (AQTC) has been proposed to acquire knowledge from videos to furnish users with comprehensive and systematic instructions.
1 code implementation • CVPR 2023 • Hengyi Wang, Jingwen Wang, Lourdes Agapito
We present Co-SLAM, a neural RGB-D SLAM system based on a hybrid representation, that performs robust camera tracking and high-fidelity surface reconstruction in real time.
no code implementations • 2 Apr 2023 • Ethan Weitkamp, Yusuke Satani, Adam Omundsen, Jingwen Wang, Peilong Li
The machine learning approach is vital in Internet of Things (IoT) malware traffic detection due to its ability to keep pace with the ever-evolving nature of malware.
1 code implementation • CVPR 2023 • Jian Li, Ziyao Meng, Daqian Shi, Rui Song, Xiaolei Diao, Jingwen Wang, Hao Xu
Through representation learning, DNNs can map BFs into dense clusters in feature space, while the features of minority classes often show sparse clusters.
1 code implementation • 12 Dec 2022 • Jinhong Wang, Jingwen Wang, Tingting Chen, Wenhao Zheng, Zhe Xu, Xingdi Wu, Wen Xu, Haochao Ying, Danny Chen, Jian Wu
Clinically, to assess the necessity of cataract surgery, accurately predicting postoperative VA before surgery by analyzing multi-view optical coherence tomography (OCT) images is crucially needed.
no code implementations • 24 Aug 2022 • Qi Lv, Ziqiang Cao, Wenrui Xie, Derui Wang, Jingwen Wang, Zhiwei Hu, Tangkun Zhang, Ba Yuan, Yuanhang Li, Min Cao, Wenjie Li, Sujian Li, Guohong Fu
Furthermore, based on the similarity between video outlines and textual outlines, we use a large number of articles with chapter headings to pretrain our model.
1 code implementation • 29 Jun 2022 • Jingwen Wang, Tymoteusz Bleja, Lourdes Agapito
We present GO-Surf, a direct feature grid optimization method for accurate and fast surface reconstruction from RGB-D sequences.
no code implementations • 23 Jun 2022 • Jiansheng Fang, Anwei Li, Pu-Yun OuYang, Jiajian Li, Jingwen Wang, Hongbo Liu, Fang-Yun Xie, Jiang Liu
We design a deep multimodal survival network (MSN) with two feature extractors to learn discriminative features from multimodal data.
1 code implementation • 7 Jun 2022 • Jiansheng Fang, Jingwen Wang, Anwei Li, Yuguang Yan, Yonghe Hou, Chao Song, Hongbo Liu, Jiang Liu
In the management of lung nodules, we are desirable to predict nodule evolution in terms of its diameter variation on Computed Tomography (CT) scans and then provide a follow-up recommendation according to the predicted result of the growing trend of the nodule.
1 code implementation • 2 Dec 2021 • Yitian Yuan, Lin Ma, Jingwen Wang, Wenwu Zhu
In this paper, we investigate a novel and challenging task, namely controllable video captioning with an exemplar sentence.
1 code implementation • 21 Aug 2021 • Jingwen Wang, Martin Rünz, Lourdes Agapito
We propose DSP-SLAM, an object-oriented SLAM system that builds a rich and accurate joint map of dense 3D models for foreground objects, and sparse landmark points to represent the background.
6 code implementations • ACL 2021 • Zijing Ou, Qinliang Su, Jianxing Yu, Bang Liu, Jingwen Wang, Ruihui Zhao, Changyou Chen, Yefeng Zheng
With the need of fast retrieval speed and small memory footprint, document hashing has been playing a crucial role in large-scale information retrieval.
1 code implementation • 1 Aug 2020 • Jing Shi, Zhiheng Li, Haitian Zheng, Yihang Xu, Tianyou Xiao, Weitao Tan, Xiaoning Guo, Sizhe Li, Bin Yang, Zhexin Xu, Ruitao Lin, Zhongkai Shangguan, Yue Zhao, Jingwen Wang, Rohan Sharma, Surya Iyer, Ajinkya Deshmukh, Raunak Mahalik, Srishti Singh, Jayant G Rohra, Yi-Peng Zhang, Tongyu Yang, Xuan Wen, Ethan Fahnestock, Bryce Ikeda, Ian Lawson, Alan Finkelstein, Kehao Guo, Richard Magnotti, Andrew Sexton, Jeet Ketan Thaker, Yiyang Su, Chenliang Xu
This technical report summarizes submissions and compiles from Actor-Action video classification challenge held as a final project in CSC 249/449 Machine Vision course (Spring 2020) at University of Rochester
1 code implementation • 21 Jul 2020 • Jinxiu Liang, Jingwen Wang, Yuhui Quan, Tianyi Chen, Jiaying Liu, Haibin Ling, Yong Xu
REG produces progressively and efficiently intermediate images corresponding to various exposure settings, and such pseudo-exposures are then fused by MED to detect faces across different lighting conditions.
no code implementations • 4 Jul 2020 • Jinxiu Liang, Yong Xu, Yuhui Quan, Jingwen Wang, Haibin Ling, Hui Ji
Low-light images, i. e. the images captured in low-light conditions, suffer from very poor visibility caused by low contrast, color distortion and significant measurement noise.
no code implementations • 18 Mar 2020 • Xu Li, Jingwen Wang, Lin Ma, Kaihao Zhang, Fengzong Lian, Zhanhui Kang, Jinjun Wang
Such a design enables efficient spatio-temporal modeling and maintains a small model scale.
no code implementations • 16 Mar 2020 • Yijun Song, Jingwen Wang, Lin Ma, Zhou Yu, Jun Yu
The task of temporally grounding textual queries in videos is to localize one video segment that semantically corresponds to the given query.
1 code implementation • 18 Dec 2019 • Richard J. Chen, Ming Y. Lu, Jingwen Wang, Drew F. K. Williamson, Scott J. Rodig, Neal I. Lindeman, Faisal Mahmood
Cancer diagnosis, prognosis, and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data.
1 code implementation • NeurIPS 2019 • Yitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu
Temporal sentence grounding in videos aims to detect and localize one target video segment, which semantically corresponds to a given sentence.
no code implementations • 29 Oct 2019 • Jingwen Wang, Richard J. Chen, Ming Y. Lu, Alexander Baras, Faisal Mahmood
In prostate cancer, the Gleason score is a grading system used to measure the aggressiveness of prostate cancer from the spatial organization of cells and the distribution of glands.
no code implementations • 23 Oct 2019 • Ming Y. Lu, Richard J. Chen, Jingwen Wang, Debora Dillon, Faisal Mahmood
Convolutional neural networks can be trained to perform histology slide classification using weak annotations with multiple instance learning (MIL).
1 code implementation • 11 Sep 2019 • Jingwen Wang, Lin Ma, Wenhao Jiang
The task of temporally grounding language queries in videos is to temporally localize the best matched video segment corresponding to a given language (sentence).
1 code implementation • ICCV 2019 • Bairui Wang, Lin Ma, Wei zhang, Wenhao Jiang, Jingwen Wang, Wei Liu
In this paper, we propose to guide the video caption generation with Part-of-Speech (POS) information, based on a gated fusion of multiple representations of input videos.
no code implementations • 17 Aug 2019 • Jingwen Wang, Hao Zhang, Cheng Zhang, Wenjing Yang, Liqun Shao, Jie Wang
To overcome this obstacle, we present NDORGS (Numerous Documents' Overview Report Generation Scheme) that integrates text filtering, keyword scoring, single-document summarization (SDS), topic modeling, MDS, and title generation to generate a coherent, well-structured ORPT.
no code implementations • 30 Jul 2019 • Jingwen Wang, Jingxin Liu, Juntao Pu, Qinghong Yang, Zhongchen Miao, Jian Gao, You Song
To improve the efficiency and accuracy of system failure detection and thereby reduce the impact of system failures on financial services, we propose a novel machine learning-based framework to predict the occurrence of system exceptions and failures in a financial software system.
no code implementations • 29 Sep 2018 • Yongyi Tang, Xing Zhang, Jingwen Wang, Shaoxiang Chen, Lin Ma, Yu-Gang Jiang
This paper describes our solution for the 2$^\text{nd}$ YouTube-8M video understanding challenge organized by Google AI.
1 code implementation • CVPR 2018 • Jingwen Wang, Wenhao Jiang, Lin Ma, Wei Liu, Yong Xu
We propose a bidirectional proposal method that effectively exploits both past and future contexts to make proposal predictions.