829 citations · 2.2k across the 40 of their papers we have counts for
25 papers · 1 filter
Unsupervised Deep Image Stitching: Reconstructing Stitched Features to Images
Lang Nie, Chunyu Lin, Kang Liao +2
Traditional feature-based image stitching technologies rely heavily on feature detection quality, often failing to stitch images with few features or low resolution. The learning-b…
Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Jimin Xiao, Jianbo Jiao +2
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmenta…
Progressively Complementary Network for Fisheye Image Rectification Using Appearance Flow
Shangrong Yang, Chunyu Lin, Kang Liao +2
Distortion rectification is often required for fisheye images. The generation-based method is one mainstream solution due to its label-free property, but its naive skip-connection…
Mining Generalized Features for Detecting AI-Manipulated Fake Faces
Yang Yu, Rongrong Ni, Yao Zhao
Recently, AI-manipulated face techniques have developed rapidly and constantly, which has raised new security issues in society. Although existing detection methods consider differ…
A Deep Ordinal Distortion Estimation Approach for Distortion Rectification
Kang Liao, Chunyu Lin, Yao Zhao
Distortion is widely existed in the images captured by popular wide-angle cameras and fisheye cameras. Despite the long history of distortion rectification, accurately estimating t…
Fast Template Matching and Update for Video Object Tracking and Segmentation
Mingjie Sun, Jimin Xiao, Eng Gee Lim +2
In this paper, the main task we aim to tackle is the multi-instance semi-supervised video object segmentation across a sequence of frames where only the first-frame box-level groun…
Deep Optimized Multiple Description Image Coding via Scalar Quantization Learning
Lijun Zhao, Huihui Bai, Anhong Wang +1
In this paper, we introduce a deep multiple description coding (MDC) framework optimized by minimizing multiple description (MD) compressive loss. First, MD multi-scale-dilated enc…
Concurrently Extrapolating and Interpolating Networks for Continuous Model Generation
Lijun Zhao, Jinjing Zhang, Fan Zhang +3
Most deep image smoothing operators are always trained repetitively when different explicit structure-texture pairs are employed as label images for each algorithm configured with…
To See in the Dark: N2DGAN for Background Modeling in Nighttime Scene
Zhenfeng Zhu, Yingying Meng, Deqiang Kong +3
Due to the deteriorated conditions of \mbox{illumination} lack and uneven lighting, nighttime images have lower contrast and higher noise than their daytime counterparts of the sam…
Progressive Sample Mining and Representation Learning for One-Shot Person Re-identification with Adversarial Samples
Hui Li, Jimin Xiao, Mingjie Sun +2
In this paper, we aim to tackle the one-shot person re-identification problem where only one image is labelled for each person, while other images are unlabelled. This task is chal…
Segmentation Mask Guided End-to-End Person Search
Dingyuan Zheng, Jimin Xiao, Kaizhu Huang +1
Person search aims to search for a target person among multiple images recorded by multiple surveillance cameras, which faces various challenges from both pedestrian detection and…
Correlation Filter Selection for Visual Tracking Using Reinforcement Learning
Yanchun Xie, Jimin Xiao, Kaizhu Huang +2
Correlation filter has been proven to be an effective tool for a number of approaches in visual tracking, particularly for seeking a good balance between tracking accuracy and spee…
Devil in the Details: Towards Accurate Single and Multiple Human Parsing
Tao Ruan, Ting Liu, Zilong Huang +4
Human parsing has received considerable interest due to its wide application potentials. Nevertheless, it is still unclear how to develop an accurate human parsing system in an eff…
Security Consideration For Deep Learning-Based Image Forensics
Wei Zhao, Pengpeng Yang, Rongrong Ni +2
Recently, image forensics community has paied attention to the research on the design of effective algorithms based on deep learning technology and facts proved that combining the…
Mixed-Resolution Image Representation and Compression with Convolutional Neural Networks
Lijun Zhao, Huihui Bai, Feng Li +2
In this paper, we propose an end-to-end mixed-resolution image compression framework with convolutional neural networks. Firstly, given one input image, feature description neural…
Learning a Virtual Codec Based on Deep Convolutional Neural Network to Compress Image
Lijun Zhao, Huihui Bai, Anhong Wang +1
Although deep convolutional neural network has been proved to efficiently eliminate coding artifacts caused by the coarse quantization of traditional codec, it's difficult to train…
Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network
Lijun Zhao, Huihui Bai, Jie Liang +3
Recently, Generative Adversarial Network (GAN) has been found wide applications in style transfer, image-to-image translation and image super-resolution. In this paper, a color-dep…
Local Activity-tuned Image Filtering for Noise Removal and Image Smoothing
Lijun Zhao, Jie Liang, Huihui Bai +3
In this paper, two local activity-tuned filtering frameworks are proposed for noise removal and image smoothing, where the local activity measurement is given by the clipped and no…
Source Camera Identification Based On Content-Adaptive Fusion Network
Pengpeng Yang, Wei Zhao, Rongrong Ni +1
Source camera identification is still a hard task in forensics community, especially for the case of the small query image size. In this paper, we propose a solution to identify th…
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach
Yunchao Wei, Jiashi Feng, Xiaodan Liang +3
We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems. Cl…
STC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation
Yunchao Wei, Xiaodan Liang, Yunpeng Chen +5
Recently, significant improvement has been made on semantic object segmentation due to the development of deep convolutional neural networks (DCNNs). Training such a DCNN usually r…
Indexing of CNN Features for Large Scale Image Search
Ruoyu Liu, Yao Zhao, Shikui Wei +1
The convolutional neural network (CNN) features can give a good description of image content, which usually represent images with unique global vectors. Although they are compact c…
Modality-dependent Cross-media Retrieval
Yunchao Wei, Yao Zhao, Zhenfeng Zhu +4
In this paper, we investigate the cross-media retrieval between images and text, i.e., using image to search text (I2T) and using text to search images (T2I). Existing cross-media…
CNN: Single-label to Multi-label
Yunchao Wei, Wei Xia, Junshi Huang +4
Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still rema…