1 code implementation • 20 Mar 2024 • Junjie Chen, Jiebin Yan, Yuming Fang, Li Niu
Existing methods only rely on the features extracted at support keypoints to predict or refine the keypoints on query image, but a few support feature vectors are local and inadequate for CAPE.
no code implementations • 2 Feb 2024 • Hanwei Zhu, Xiangjie Sui, Baoliang Chen, Xuelin Liu, Peilin Chen, Yuming Fang, Shiqi Wang
While abundant research has been conducted on improving high-level visual understanding and reasoning capabilities of large multimodal models~(LMMs), their visual quality assessment~(IQA) ability has been relatively under-explored.
1 code implementation • 7 Sep 2023 • Xiangjie Sui, Hanwei Zhu, Xuelin Liu, Yuming Fang, Shiqi Wang, Zhou Wang
To address these issues, we introduce a unique generative scanpath representation (GSR) for effective quality inference of 360$^\circ$ images, which aggregates varied perceptual experiences of multi-hypothesis users under a predefined viewing condition.
no code implementations • 29 Jun 2023 • Weide Liu, Xiaoyang Zhong, Jingwen Hou, Shaohua Li, Haozhe Huang, Yuming Fang
Multimodal Named Entity Recognition (MNER) is a crucial task for information extraction from social media platforms such as Twitter.
1 code implementation • 24 Mar 2023 • Weide Liu, Zhonghua Wu, Yang Zhao, Yuming Fang, Chuan-Sheng Foo, Jun Cheng, Guosheng Lin
Current methods for few-shot segmentation (FSSeg) have mainly focused on improving the performance of novel classes while neglecting the performance of base classes.
1 code implementation • CVPR 2023 • Xiangjie Sui, Yuming Fang, Hanwei Zhu, Shiqi Wang, Zhou Wang
Scanpath prediction for 360deg images aims to produce dynamic gaze behaviors based on the human visual perception mechanism.
no code implementations • 26 Nov 2022 • Yifan Zuo, Jiacheng Xie, Yuming Fang, Yan Huang, Wenhui Jiang
A mainstream type of the state of the arts (SOTAs) based on convolutional neural network (CNN) for real image denoising contains two sub-problems, i. e., noise estimation and non-blind denoising.
1 code implementation • 1 Nov 2022 • Xiaoshui Huang, Wentao Qu, Yifan Zuo, Yuming Fang, Xiaowei Zhao
In this paper, we propose General Multimodal Fusion (GMF) to learn to reject the correspondence outliers by leveraging both the structure and texture information.
no code implementations • 20 Jun 2022 • Chenglizhao Chen, Hengsen Wang, Yuming Fang, Chong Peng
The existing state-of-the-art (SOTA) video salient object detection (VSOD) models have widely followed short-term methodology, which dynamically determines the balance between spatial and temporal saliency fusion by solely considering the current consecutive limited frames.
no code implementations • 18 Jun 2022 • Peibei Cao, Chenyang Le, Yuming Fang, Kede Ma
In Stage two, the input HDR image is self-calibrated to compute the final LDR image.
1 code implementation • 13 Jun 2022 • Wen Wen, Mu Li, Yiru Yao, Xiangjie Sui, Yabin Zhang, Long Lan, Yuming Fang, Kede Ma
Investigating how people perceive virtual reality (VR) videos in the wild (i. e., those captured by everyday users) is a crucial and challenging task in VR-related applications due to complex authentic distortions localized in space and time.
no code implementations • 2 Jun 2022 • Jingwen Hou, Henghui Ding, Weisi Lin, Weide Liu, Yuming Fang
To deal with this dilemma, we propose to distill knowledge on semantic patterns for a vast variety of image contents from multiple pre-trained object classification (POC) models to an IAA model.
1 code implementation • 26 May 2022 • Zhihua Wang, Keshuo Xu, Yang Yang, Jianlei Dong, Shuhang Gu, Lihao Xu, Yuming Fang, Kede Ma
Measuring perceptual color differences (CDs) is of great importance in modern smartphone photography.
1 code implementation • 18 Nov 2021 • Xiaoshui Huang, Wentao Qu, Yifan Zuo, Yuming Fang, Xiaowei Zhao
In this paper, we propose a new multimodal fusion method to generate a point cloud registration descriptor by considering both structure and texture information.
Ranked #1 on Point Cloud Registration on 3DMatch Benchmark (using extra training data)
no code implementations • 19 Oct 2021 • Kede Ma, Yuming Fang
This tutorial provides the audience with the basic theories, methodologies, and current progresses of image quality assessment (IQA).
no code implementations • 1 Sep 2021 • Chenyang Le, Jiebin Yan, Yuming Fang, Kede Ma
We describe a deep high-dynamic-range (HDR) image tone mapping operator that is computationally efficient and perceptually optimized.
1 code implementation • 16 Jun 2021 • Boyang Wan, Wenhui Jiang, Yuming Fang, Zhiyuan Luo, Guanqun Ding
2) It provides the annotation data, including video-level labels (abnormal/normal video, anomaly type) and frame-level labels (abnormal/normal video frame) to facilitate anomaly detection.
1 code implementation • 15 Apr 2021 • Boyang Wan, Yuming Fang, Xue Xia, Jiajie Mei
Anomaly detection in surveillance videos is a challenging task due to the diversity of anomalous video content and duration.
Anomaly Detection In Surveillance Videos Multiple Instance Learning +2
1 code implementation • 27 Feb 2021 • Jiebin Yan, Yu Zhong, Yuming Fang, Zhangyang Wang, Kede Ma
A natural question then arises: Does the superior performance on the closed (and frequently re-used) test sets transfer to the open visual world with unconstrained variations?
3 code implementations • 26 Nov 2020 • Qijian Zhang, Runmin Cong, Chongyi Li, Ming-Ming Cheng, Yuming Fang, Xiaochun Cao, Yao Zhao, Sam Kwong
Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains an open and challenging problem.
no code implementations • 5 Nov 2020 • Wenying Wen, Rongxin Tu, Yushu Zhang, Yuming Fang, Yong Yang
High-efficiency video coding (HEVC) encryption has been proposed to encrypt syntax elements for the purpose of video encryption.
1 code implementation • 7 Aug 2020 • Chenglizhao Chen, Guotao Wang, Chong Peng, Dingwen Zhang, Yuming Fang, Hong Qin
In this way, even though the overall video saliency quality is heavily dependent on its spatial branch, however, the performance of the temporal branch still matter.
1 code implementation • 7 Aug 2020 • Xuehao Wang, Shuai Li, Chenglizhao Chen, Yuming Fang, Aimin Hao, Hong Qin
Existing RGB-D salient object detection methods treat depth information as an independent component to complement its RGB part, and widely follow the bi-stream parallel network architecture.
1 code implementation • 7 Aug 2020 • Chenglizhao Chen, Jia Song, Chong Peng, Guodong Wang, Yuming Fang
Consequently, we can achieve a significant performance improvement by using this new training set to start a new round of network training.
1 code implementation • CVPR 2020 • Yuming Fang, Hanwei Zhu, Yan Zeng, Kede Ma, Zhou Wang
As smartphones become people's primary cameras to take photos, the quality of their cameras and the associated computational photography modules has become a de facto standard in evaluating and ranking smartphones in the consumer market.
Ranked #4 on Image Quality Assessment on MSU NR VQA Database
2 code implementations • 21 May 2020 • Xiangjie Sui, Kede Ma, Yiru Yao, Yuming Fang
We first carry out a psychophysical experiment to investigate the interplay among the VR viewing conditions, the user viewing behaviors, and the perceived quality of 360{\deg} images.
no code implementations • 16 Dec 2019 • Wenhan Yang, Robby T. Tan, Shiqi Wang, Yuming Fang, Jiaying Liu
The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation.
1 code implementation • 28 Feb 2019 • Nevrez Imamoglu, Guanqun Ding, Yuming Fang, Asako Kanezaki, Toru Kouyama, Ryosuke Nakamura
Various saliency detection algorithms from color images have been proposed to mimic eye fixation or attentive object detection response of human observers for the same scenes.
no code implementations • 12 Jul 2018 • Guanqun Ding, Yuming Fang
Different from salient object detection methods for still images, a key challenging for video saliency detection is how to extract and combine spatial and temporal features.
1 code implementation • 12 Jul 2018 • Yuming Fang, Guanqun Ding, Yuan Yuan, Weisi Lin, Haiwen Liu
In this study, we conduct the research on the robustness of pedestrian detection algorithms to video quality degradation.
no code implementations • 4 Jul 2018 • Nevrez Imamoglu, Wataru Shimoda, Chi Zhang, Yuming Fang, Asako Kanezaki, Keiji Yanai, Yoshifumi Nishida
Bottom-up and top-down visual cues are two types of information that helps the visual saliency models.
2 code implementations • 29 Jun 2018 • Nevrez Imamoglu, Yu Oishi, Xiaoqiang Zhang, Guanqun Ding, Yuming Fang, Toru Kouyama, Ryosuke Nakamura
Many works have been done on salient object detection using supervised or unsupervised approaches on colour images.
1 code implementation • 1 Mar 2017 • Nevrez Imamoglu, Chi Zhang, Wataru Shimoda, Yuming Fang, Boxin Shi
As prior knowledge of objects or object features helps us make relations for similar objects on attentional tasks, pre-trained deep convolutional neural networks (CNNs) can be used to detect salient objects on images regardless of the object class is in the network knowledge or not.