175 citations · 1.3k across the 83 of their papers we have counts for
11 papers · 1 filter
From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur
Dong Gong, Jie Yang, Lingqiao Liu +5
Removing pixel-wise heterogeneous motion blur is challenging due to the ill-posed nature of the problem. The predominant solution is to estimate the blur kernel by adding a prior,…
Sequential Person Recognition in Photo Albums with a Recurrent Network
Yao Li, Guosheng Lin, Bohan Zhuang +3
Recognizing the identities of people in everyday photos is still a very challenging problem for machine vision, due to non-frontal faces, changes in clothing, location, lighting an…
Attend in groups: a weakly-supervised deep learning framework for learning from web data
Bohan Zhuang, Lingqiao Liu, Yao Li +2
Large-scale datasets have driven the rapid development of deep neural networks for visual recognition. However, annotating a massive dataset is expensive and time-consuming. Web im…
Graph-Structured Representations for Visual Question Answering
Damien Teney, Lingqiao Liu, Anton van den Hengel
This paper proposes to improve visual question answering (VQA) with structured representations of both scene contents and questions. A key challenge in VQA is to require joint reas…
Exploiting Temporal Information for DCNN-based Fine-Grained Object Classification
ZongYuan Ge, Chris McCool, Conrad Sanderson +4
Fine-grained classification is a relatively new field that has concentrated on using information from a single image, while ignoring the enormous potential of using video data to i…
Where to Focus: Query Adaptive Matching for Instance Retrieval Using Convolutional Feature Maps
Jiewei Cao, Lingqiao Liu, Peng Wang +3
Instance retrieval requires one to search for images that contain a particular object within a large corpus. Recent studies show that using image features generated by pooling conv…
Less is more: zero-shot learning from online textual documents with noise suppression
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen +1
Classifying a visual concept merely from its associated online textual source, such as a Wikipedia article, is an attractive research topic in zero-shot learning because it allevia…
Image Co-localization by Mimicking a Good Detector's Confidence Score Distribution
Yao Li, Linqiao Liu, Chunhua Shen +1
Given a set of images containing objects from the same category, the task of image co-localization is to identify and localize each instance. This paper shows that this problem can…
Hi Detector, What's Wrong with that Object? Identifying Irregular Object From Images by Modelling the Detection Score Distribution
Peng Wang, Lingqiao Liu, Chunhua Shen +2
In this work, we study the challenging problem of identifying the irregular status of objects from images in an "open world" setting, that is, distinguishing the irregular status o…
Order-aware Convolutional Pooling for Video Based Action Recognition
Peng Wang, Lingqiao Liu, Chunhua Shen +1
Most video based action recognition approaches create the video-level representation by temporally pooling the features extracted at each frame. The pooling methods that they adopt…
Compositional Model based Fisher Vector Coding for Image Classification
Lingqiao Liu, Peng Wang, Chunhua Shen +4
Deriving from the gradient vector of a generative model of local features, Fisher vector coding (FVC) has been identified as an effective coding method for image classification. Mo…