416 citations · 2.7k across the 106 of their papers we have counts for
14 papers · 1 filter
Self-Enhanced Convolutional Network for Facial Video Hallucination
Chaowei Fang, Guanbin Li, Xiaoguang Han +1
As a domain-specific super-resolution problem, facial image hallucination has enjoyed a series of breakthroughs thanks to the advances of deep convolutional neural networks. Howeve…
Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation
Chaowei Fang, Guanbin Li, Chengwei Pan +2
Recently 3D volumetric organ segmentation attracts much research interest in medical image analysis due to its significance in computer aided diagnosis. This paper aims to address…
Motion Guided Attention for Video Salient Object Detection
Haofeng Li, Guanqi Chen, Guanbin Li +1
Video salient object detection aims at discovering the most visually distinctive objects in a video. How to effectively take object motion into consideration during video salient o…
Dynamic Graph Attention for Referring Expression Comprehension
Sibei Yang, Guanbin Li, Yizhou Yu
Referring expression comprehension aims to locate the object instance described by a natural language referring expression in an image. This task is compositional and inherently re…
MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection
Zihao Li, Shu Zhang, Junge Zhang +3
Universal lesion detection (ULD) on computed tomography (CT) images is an important but underdeveloped problem. Recently, deep learning-based approaches have been proposed for ULD,…
Relationship-Embedded Representation Learning for Grounding Referring Expressions
Sibei Yang, Guanbin Li, Yizhou Yu
Grounding referring expressions in images aims to locate the object instance in an image described by a referring expression. It involves a joint understanding of natural language…
ROSA: Robust Salient Object Detection against Adversarial Attacks
Haofeng Li, Guanbin Li, Yizhou Yu
Recently salient object detection has witnessed remarkable improvement owing to the deep convolutional neural networks which can harvest powerful features for images. In particular…
Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks
Xiang He, Sibei Yang, Guanbin Li? +3
Recent progress in biomedical image segmentation based on deep convolutional neural networks (CNNs) has drawn much attention. However, its vulnerability towards adversarial samples…
A Benchmark for Edge-Preserving Image Smoothing
Feida Zhu, Zhetong Liang, Xixi Jia +2
Edge-preserving image smoothing is an important step for many low-level vision problems. Though many algorithms have been proposed, there are several difficulties hindering its fur…
Harvesting Visual Objects from Internet Images via Deep Learning Based Objectness Assessment
Kan Wu, Guanbin Li, Haofeng Li +2
The collection of internet images has been growing in an astonishing speed. It is undoubted that these images contain rich visual information that can be useful in many application…
Multi-source weak supervision for saliency detection
Yu Zeng, Yunzhi Zhuge, Huchuan Lu +3
The high cost of pixel-level annotations makes it appealing to train saliency detection models with weak supervision. However, a single weak supervision source usually does not con…
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation
Huikai Wu, Junge Zhang, Kaiqi Huang +2
Modern approaches for semantic segmentation usually employ dilated convolutions in the backbone to extract high-resolution feature maps, which brings heavy computation complexity a…
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom Up
Weifeng Ge, Xiangru Lin, Yizhou Yu
Given a training dataset composed of images and corresponding category labels, deep convolutional neural networks show a strong ability in mining discriminative parts for image cla…
Transductive Zero-Shot Learning with Visual Structure Constraint
Ziyu Wan, Dongdong Chen, Yan Li +4
To recognize objects of the unseen classes, most existing Zero-Shot Learning(ZSL) methods first learn a compatible projection function between the common semantic space and the vis…