no code implementations • 4 Jun 2025 • Xiansheng Cai, Sihan Hu, Tao Wang, Yuan Huang, Pan Zhang, Youjin Deng, Kun Chen
Fundamental physics often confronts complex symbolic problems with few guiding exemplars or established principles.
no code implementations • 29 May 2025 • Tianhang Wang, Fan Lu, Sanqing Qu, Guo Yu, Shihang Du, Ya Wu, Yuan Huang, Guang Chen
Existing neural rendering-based urban scene reconstruction methods mainly focus on the Interpolated View Synthesis (IVS) setting that synthesizes from views close to training camera trajectory.
no code implementations • 21 Mar 2025 • Miao Ye, Jihao Zheng, Qiuxiang Jiang, Yuan Huang, Ziheng Wang, Yong Wang
The existing segment routing (SR) methods need to determine the routing first and then use path segmentation approaches to select swap nodes to form a segment routing path (SRP).
1 code implementation • 19 Feb 2025 • Zirui Song, Jingpu Yang, Yuan Huang, Jonathan Tonglet, Zeyu Zhang, Tao Cheng, Meng Fang, Iryna Gurevych, Xiuying Chen
To address these challenges, we introduce a comprehensive geolocation framework with three key components: GeoComp, a large-scale dataset; GeoCoT, a novel reasoning method; and GeoEval, an evaluation metric, collectively designed to address critical challenges and drive advancements in geolocation research.
1 code implementation • 17 Feb 2025 • Jianyi Peng, Fan Lu, Bin Li, Yuan Huang, Sanqing Qu, Guang Chen
Compared to single-modal VPR, this approach benefits from the widespread availability of RGB cameras and the robustness of point clouds in providing accurate spatial geometry and distance information.
no code implementations • 11 Feb 2025 • Xueyao Zhang, Xiaohui Zhang, Kainan Peng, Zhenyu Tang, Vimal Manohar, Yingru Liu, Jeff Hwang, Dangna Li, Yuhao Wang, Julian Chan, Yuan Huang, Zhizheng Wu, Mingbo Ma
However, existing methods rely heavily on annotated data, and struggle with effectively disentangling timbre and style, leading to challenges in achieving controllable generation, especially in zero-shot scenarios.
no code implementations • 24 Jan 2025 • Xu Chen, Yuan Huang, Benn Jessney, Jason Sangha, Sophie Gu, Carola-Bibiane Schönlieb, Martin Bennett, Michael Roberts
Artificial intelligence (AI) methodologies hold great promise for the rapid and accurate diagnosis of coronary artery disease (CAD) from intravascular optical coherent tomography (IVOCT) images.
no code implementations • 3 Dec 2024 • ZhiYuan Chen, Fan Lu, Guo Yu, Bin Li, Sanqing Qu, Yuan Huang, Changhong Fu, Guang Chen
Tracking the 6DoF pose of unknown objects in monocular RGB video sequences is crucial for robotic manipulation.
no code implementations • 28 Oct 2024 • Yuan Huang, Fugen Zhou, Jerome Gilles
In this paper, we propose a new approach to perform supervised texture classification/segmentation.
no code implementations • 24 Oct 2024 • Yuan Huang, Valentin De Bortoli, Fugen Zhou, Jerome Gilles
Wavelet-based segmentation approaches are widely used for texture segmentation purposes because of their ability to characterize different textures.
1 code implementation • 8 May 2024 • Yaqi Wu, Zhihao Fan, Xiaofeng Chu, Jimmy S. Ren, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangcheng Zhou, Ruicheng Feng, Yuekun Dai, Peiqing Yang, Chen Change Loy, Senyan Xu, Zhijing Sun, Jiaying Zhu, Yurui Zhu, Xueyang Fu, Zheng-Jun Zha, Jun Cao, Cheng Li, Shu Chen, Liang Ma, Shiyang Zhou, Haijin Zeng, Kai Feng, Yongyong Chen, Jingyong Su, Xianyu Guan, Hongyuan Yu, Cheng Wan, Jiamin Lin, Binnan Han, Yajun Zou, Zhuoyuan Wu, Yuan Huang, Yongsheng Yu, Daoan Zhang, Jizhe Li, Xuanwu Yin, Kunlong Zuo, Yunfan Lu, Yijie Xu, Wenzong Ma, Weiyu Guo, Hui Xiong, Wei Yu, Bingchun Luo, Sabari Nathan, Priya Kansal
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
no code implementations • 28 Apr 2024 • Zirui Song, Yaohang Li, Meng Fang, Yanda Li, Zhenhao Chen, Zecheng Shi, Yuan Huang, Xiuying Chen, Ling Chen
To address this, we propose the Multi-Modal Agent Collaboration framework (MMAC-Copilot), a framework utilizes the collective expertise of diverse agents to enhance interaction ability with application.
2 code implementations • 25 Apr 2024 • Marcos V. Conde, Zhijun Lei, Wen Li, Cosmin Stejerean, Ioannis Katsavounidis, Radu Timofte, Kihwan Yoon, Ganzorig Gankhuyag, Jiangtao Lv, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Zhiyuan Li, Hao Wei, Chenyang Ge, Dongyang Zhang, Tianle Liu, Huaian Chen, Yi Jin, Menghan Zhou, Yiqiang Yan, Si Gao, Biao Wu, Shaoli Liu, Chengjian Zheng, Diankai Zhang, Ning Wang, Xintao Qiu, Yuanbo Zhou, Kongxian Wu, Xinwei Dai, Hui Tang, Wei Deng, Qingquan Gao, Tong Tong, Jae-Hyeon Lee, Ui-Jin Choi, Min Yan, Xin Liu, Qian Wang, Xiaoqian Ye, Zhan Du, Tiansen Zhang, Long Peng, Jiaming Guo, Xin Di, Bohao Liao, Zhibo Du, Peize Xia, Renjing Pei, Yang Wang, Yang Cao, ZhengJun Zha, Bingnan Han, Hongyuan Yu, Zhuoyuan Wu, Cheng Wan, Yuqing Liu, Haodong Yu, Jizhe Li, Zhijuan Huang, Yuan Huang, Yajun Zou, Xianyu Guan, Qi Jia, Heng Zhang, Xuanwu Yin, Kunlong Zuo, Hyeon-Cheol Moon, Tae-hyun Jeong, Yoonmo Yang, Jae-Gon Kim, Jinwoo Jeong, Sunjei Kim
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs.
1 code implementation • 15 Apr 2024 • Zheng Chen, Zongwei Wu, Eduard Zamfir, Kai Zhang, Yulun Zhang, Radu Timofte, Xiaokang Yang, Hongyuan Yu, Cheng Wan, Yuxin Hong, Zhijuan Huang, Yajun Zou, Yuan Huang, Jiamin Lin, Bingnan Han, Xianyu Guan, Yongsheng Yu, Daoan Zhang, Xuanwu Yin, Kunlong Zuo, Jinhua Hao, Kai Zhao, Kun Yuan, Ming Sun, Chao Zhou, Hongyu An, Xinfeng Zhang, Zhiyuan Song, Ziyue Dong, Qing Zhao, Xiaogang Xu, Pengxu Wei, Zhi-chao Dou, Gui-ling Wang, Chih-Chung Hsu, Chia-Ming Lee, Yi-Shiuan Chou, Cansu Korkmaz, A. Murat Tekalp, Yubin Wei, Xiaole Yan, Binren Li, Haonan Chen, Siqi Zhang, Sihan Chen, Amogh Joshi, Nikhil Akalwadi, Sampada Malagi, Palani Yashaswini, Chaitra Desai, Ramesh Ashok Tabib, Ujwala Patil, Uma Mudenagudi, Anjali Sarvaiya, Pooja Choksy, Jagrit Joshi, Shubh Kawa, Kishor Upla, Sushrut Patwardhan, Raghavendra Ramachandra, Sadat Hossain, Geongi Park, S. M. Nadim Uddin, Hao Xu, Yanhui Guo, Aman Urumbekov, Xingzhuo Yan, Wei Hao, Minghan Fu, Isaac Orais, Samuel Smith, Ying Liu, Wangwang Jia, Qisheng Xu, Kele Xu, Weijun Yuan, Zhan Li, Wenqin Kuang, Ruijin Guan, Ruting Deng, Zhao Zhang, Bo wang, Suiyi Zhao, Yan Luo, Yanyan Wei, Asif Hussain Khan, Christian Micheloni, Niki Martinel
This paper reviews the NTIRE 2024 challenge on image super-resolution ($\times$4), highlighting the solutions proposed and the outcomes obtained.
no code implementations • 20 Dec 2023 • Guodong Du, HaoJian Deng, Jiahao Su, Yuan Huang
To be specific, we generate rainy RAW data by converting color rain streak into RAW space and design simple but efficient RAW processing algorithms to synthesize both rainy and clean color images.
no code implementations • 28 Nov 2023 • Wang Zhu, Ishika Singh, Yuan Huang, Robin Jia, Jesse Thomason
Data augmentation via back-translation is common when pretraining Vision-and-Language Navigation (VLN) models, even though the generated instructions are noisy.
1 code implementation • 17 May 2023 • Boying Li, Danping Zou, Yuan Huang, Xinghan Niu, Ling Pei, Wenxian Yu
The results show that integrating texture features leads to a more superior SLAM system that can match images across day and night.
1 code implementation • 21 Oct 2022 • Haochen Li, Chunyan Miao, Cyril Leung, Yanxian Huang, Yuan Huang, Hongyu Zhang, Yanlin Wang
In this paper, we explore augmentation methods that augment data (both code and query) at representation level which does not require additional data processing and training, and based on this we propose a general format of representation-level augmentation that unifies existing methods.
1 code implementation • ICCV 2021 • Boying Li, Yuan Huang, Zeyu Liu, Danping Zou, Wenxian Yu
Inspired by the early works on indoor modeling, we leverage the structural regularities exhibited in indoor scenes, to train a better depth network.
no code implementations • 20 Jan 2021 • Tao Wei, Angelica I Aviles-Rivero, Shuo Wang, Yuan Huang, Fiona J Gilbert, Carola-Bibiane Schönlieb, Chang Wen Chen
The current state-of-the-art approaches for medical image classification rely on using the de-facto method for ConvNets - fine-tuning.
Cancer-no cancer per image classification
image-classification
+4
no code implementations • 28 May 2020 • Yuan Huang, YUXING XIANG, RUIXIAO ZHAO, AND ZHE CHEN
Predicting urban air quality is a significant aspect of preventing urban air pollution and improving the living environment of urban residents.
1 code implementation • 17 Jun 2019 • Jun Xu, Yuan Huang, Ming-Ming Cheng, Li Liu, Fan Zhu, Zhou Xu, Ling Shao
A simple but useful observation on our NAC is: as long as the noise is weak, it is feasible to learn a self-supervised network only with the corrupted image, approximating the optimal parameters of a supervised network learned with pairs of noisy and clean images.