348 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- City University of Hong KongHK5 papers
- National Institute of Advanced Industrial Science and TechnologyJP4 papers
- Chinese Academy of SciencesCN3 papers
- Michigan State UniversityUS3 papers
- Nanyang Technological UniversitySG3 papers
- Swansea UniversityGB3 papers
- Academy of Mathematics and Systems ScienceCN2 papers
- Beijing University of Posts and TelecommunicationsCN2 papers
- Gannan Normal UniversityCN2 papers
- Nanjing University of Aeronautics and AstronauticsCN2 papers
- Nankai UniversityCN2 papers
- Southwest UniversityCN2 papers
14 papers · 1 filter
Superpixel-informed Implicit Neural Representation for Multi-Dimensional Data
Jiayi Li, Xile Zhao, Jianli Wang +2
Recently, implicit neural representations (INRs) have attracted increasing attention for multi-dimensional data recovery. However, INRs simply map coordinates via a multi-layer per…
Representing Noisy Image Without Denoising
Shuren Qi, Yushu Zhang, Chao Wang +3
A long-standing topic in artificial intelligence is the effective recognition of patterns from noisy images. In this regard, the recent data-driven paradigm considers 1) improving…
Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning
Boyang Wan, Yuming Fang, Xue Xia +1
Anomaly detection in surveillance videos is a challenging task due to the diversity of anomalous video content and duration. In this paper, we consider video anomaly detection as a…
Exposing Semantic Segmentation Failures via Maximum Discrepancy Competition
Jiebin Yan, Yu Zhong, Yuming Fang +2
Semantic segmentation is an extensively studied task in computer vision, with numerous methods proposed every year. Thanks to the advent of deep learning in semantic segmentation,…
Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images
Qijian Zhang, Runmin Cong, Chongyi Li +5
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 a…
Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection
Xuehao Wang, Shuai Li, Chenglizhao Chen +3
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 arc…
Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection
Chenglizhao Chen, Guotao Wang, Chong Peng +3
The current main stream methods formulate their video saliency mainly from two independent venues, i.e., the spatial and temporal branches. As a complementary component, the main t…
Salient object detection on hyperspectral images using features learned from unsupervised segmentation task
Nevrez Imamoglu, Guanqun Ding, Yuming Fang +3
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. Howe…
Deep Smoke Segmentation
Feiniu Yuan, Lin Zhang, Xue Xia +3
Inspired by the recent success of fully convolutional networks (FCN) in semantic segmentation, we propose a deep smoke segmentation network to infer high quality segmentation masks…
Robustness Analysis of Pedestrian Detectors for Surveillance
Yuming Fang, Guanqun Ding, Yuan Yuan +2
To obtain effective pedestrian detection results in surveillance video, there have been many methods proposed to handle the problems from severe occlusion, pose variation, clutter…
Video Saliency Detection by 3D Convolutional Neural Networks
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. In thi…
An Integration of Bottom-up and Top-Down Salient Cues on RGB-D Data: Saliency from Objectness vs. Non-Objectness
Nevrez Imamoglu, Wataru Shimoda, Chi Zhang +4
Bottom-up and top-down visual cues are two types of information that helps the visual saliency models. These salient cues can be from spatial distributions of the features (space-b…
Hyperspectral Image Dataset for Benchmarking on Salient Object Detection
Nevrez Imamoglu, Yu Oishi, Xiaoqiang Zhang +4
Many works have been done on salient object detection using supervised or unsupervised approaches on colour images. Recently, a few studies demonstrated that efficient salient obje…
Saliency Detection by Forward and Backward Cues in Deep-CNNs
Nevrez Imamoglu, Chi Zhang, Wataru Shimoda +2
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…