348 citations · 678 across the 31 of their papers we have counts for
22 papers · 1 filter
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation
Weide Liu, Zhonghua Wu, Yang Zhao +4
Current methods for few-shot segmentation (FSSeg) have mainly focused on improving the performance of novel classes while neglecting the performance of base classes. To overcome th…
GMF: General Multimodal Fusion Framework for Correspondence Outlier Rejection
Xiaoshui Huang, Wentao Qu, Yifan Zuo +2
Rejecting correspondence outliers enables to boost the correspondence quality, which is a critical step in achieving high point cloud registration accuracy. The current state-of-th…
A Novel Long-term Iterative Mining Scheme for Video Salient Object Detection
Chenglizhao Chen, Hengsen Wang, Yuming Fang +1
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 spat…
Perceptual Quality Assessment of Virtual Reality Videos in the Wild
Wen Wen, Mu Li, Yiru Yao +5
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…
Measuring Perceptual Color Differences of Smartphone Photographs
Zhihua Wang, Keshuo Xu, Yang Yang +5
Measuring perceptual color differences (CDs) is of great importance in modern smartphone photography. Despite the long history, most CD measures have been constrained by psychophys…
IMFNet: Interpretable Multimodal Fusion for Point Cloud Registration
Xiaoshui Huang, Wentao Qu, Yifan Zuo +2
The existing state-of-the-art point descriptor relies on structure information only, which omit the texture information. However, texture information is crucial for our humans to d…
Image Quality Assessment in the Modern Age
Kede Ma, Yuming Fang
This tutorial provides the audience with the basic theories, methodologies, and current progresses of image quality assessment (IQA). From an actionable perspective, we will first…
Perceptually Optimized Deep High-Dynamic-Range Image Tone Mapping
Chenyang Le, Jiebin Yan, Yuming Fang +1
We describe a deep high-dynamic-range (HDR) image tone mapping operator that is computationally efficient and perceptually optimized. We first decompose an HDR image into a normali…
Anomaly Detection in Video Sequences: A Benchmark and Computational Model
Boyang Wan, Wenhui Jiang, Yuming Fang +2
Anomaly detection has attracted considerable search attention. However, existing anomaly detection databases encounter two major problems. Firstly, they are limited in scale. Secon…
Guidance and Teaching Network for Video Salient Object Detection
Yingxia Jiao, Xiao Wang, Yu-Cheng Chou +4
Owing to the difficulties of mining spatial-temporal cues, the existing approaches for video salient object detection (VSOD) are limited in understanding complex and noisy scenario…
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…
A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception
Chenglizhao Chen, Jia Song, Chong Peng +2
Previous video salient object detection (VSOD) approaches have mainly focused on designing fancy networks to achieve their performance improvements. However, with the slow-down in…
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…
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…