1.3k citations · 1.4k across the 16 of their papers we have counts for
16 papers
Feature Flow: In-network Feature Flow Estimation for Video Object Detection
Ruibing Jin, Guosheng Lin, Changyun Wen +2
Optical flow, which expresses pixel displacement, is widely used in many computer vision tasks to provide pixel-level motion information. However, with the remarkable progress of t…
CRNet: Cross-Reference Networks for Few-Shot Segmentation
Weide Liu, Chi Zhang, Guosheng Lin +1
Over the past few years, state-of-the-art image segmentation algorithms are based on deep convolutional neural networks. To render a deep network with the ability to understand a c…
Towards Robust Curve Text Detection with Conditional Spatial Expansion
Zichuan Liu, Guosheng Lin, Sheng Yang +3
It is challenging to detect curve texts due to their irregular shapes and varying sizes. In this paper, we first investigate the deficiency of the existing curve detection methods…
CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning
Chi Zhang, Guosheng Lin, Fayao Liu +2
Recent progress in semantic segmentation is driven by deep Convolutional Neural Networks and large-scale labeled image datasets. However, data labeling for pixel-wise segmentation…
Correlation Propagation Networks for Scene Text Detection
Zichuan Liu, Guosheng Lin, Wang Ling Goh +3
In this work, we propose a novel hybrid method for scene text detection namely Correlation Propagation Network (CPN). It is an end-to-end trainable framework engined by advanced Co…
Structured Learning of Tree Potentials in CRF for Image Segmentation
Fayao Liu, Guosheng Lin, Ruizhi Qiao +1
We propose a new approach to image segmentation, which exploits the advantages of both conditional random fields (CRFs) and decision trees. In the literature, the potential functio…
Structured Learning of Binary Codes with Column Generation
Guosheng Lin, Fayao Liu, Chunhua Shen +2
Hashing methods aim to learn a set of hash functions which map the original features to compact binary codes with similarity preserving in the Hamming space. Hashing has proven a v…
Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss
Fayao Liu, Guosheng Lin, Chunhua Shen
Recent works on deep conditional random fields (CRF) have set new records on many vision tasks involving structured predictions. Here we propose a fully-connected deep continuous C…
CRF Learning with CNN Features for Image Segmentation
Fayao Liu, Guosheng Lin, Chunhua Shen
Conditional Random Rields (CRF) have been widely applied in image segmentations. While most studies rely on hand-crafted features, we here propose to exploit a pre-trained large co…
Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
Fayao Liu, Chunhua Shen, Guosheng Lin +1
In this article, we tackle the problem of depth estimation from single monocular images. Compared with depth estimation using multiple images such as stereo depth perception, depth…
Deep Convolutional Neural Fields for Depth Estimation from a Single Image
Fayao Liu, Chunhua Shen, Guosheng Lin
We consider the problem of depth estimation from a single monocular image in this work. It is a challenging task as no reliable depth cues are available, e.g., stereo correspondenc…
Learning Deep Convolutional Features for MRI Based Alzheimer's Disease Classification
Fayao Liu, Chunhua Shen
Effective and accurate diagnosis of Alzheimer's disease (AD) or mild cognitive impairment (MCI) can be critical for early treatment and thus has attracted more and more attention n…
From Kernel Machines to Ensemble Learning
Chunhua Shen, Fayao Liu
Ensemble methods such as boosting combine multiple learners to obtain better prediction than could be obtained from any individual learner. Here we propose a principled framework f…
Online Unsupervised Feature Learning for Visual Tracking
Fayao Liu, Chunhua Shen, Ian Reid +1
Feature encoding with respect to an over-complete dictionary learned by unsupervised methods, followed by spatial pyramid pooling, and linear classification, has exhibited powerful…
Multiple Kernel Learning in the Primal for Multi-modal Alzheimer's Disease Classification
Fayao Liu, Luping Zhou, Chunhua Shen +1
To achieve effective and efficient detection of Alzheimer's disease (AD), many machine learning methods have been introduced into this realm. However, the general case of limited t…
An Efficient Dual Approach to Distance Metric Learning
Chunhua Shen, Junae Kim, Fayao Liu +2
Distance metric learning is of fundamental interest in machine learning because the distance metric employed can significantly affect the performance of many learning methods. Quad…