Recent advances and trends in visual tracking: A review
The goal of this paper is to review the state-of-the-art progress on visual tracking methods,
classify them into different categories, as well as identify future trends. Visual tracking is a …
classify them into different categories, as well as identify future trends. Visual tracking is a …
Data-driven graph construction and graph learning: A review
A graph is one of important mathematical tools to describe ubiquitous relations. In the
classical graph theory and some applications, graphs are generally provided in advance, or …
classical graph theory and some applications, graphs are generally provided in advance, or …
Video question answering via gradually refined attention over appearance and motion
Recently image question answering (ImageQA) has gained lots of attention in the research
community. However, as its natural extension, video question answering (VideoQA) is less …
community. However, as its natural extension, video question answering (VideoQA) is less …
[PDF][PDF] Parameter-free auto-weighted multiple graph learning: A framework for multiview clustering and semi-supervised classification.
Graph-based approaches have been successful in unsupervised and semi-supervised
learning. In this paper, we focus on the real-world applications where the same instance can …
learning. In this paper, we focus on the real-world applications where the same instance can …
Survey on deep multi-modal data analytics: Collaboration, rivalry, and fusion
Y Wang - ACM Transactions on Multimedia Computing …, 2021 - dl.acm.org
With the development of web technology, multi-modal or multi-view data has surged as a
major stream for big data, where each modal/view encodes individual property of data …
major stream for big data, where each modal/view encodes individual property of data …
Cross-modal retrieval with CNN visual features: A new baseline
Recently, convolutional neural network (CNN) visual features have demonstrated their
powerful ability as a universal representation for various recognition tasks. In this paper …
powerful ability as a universal representation for various recognition tasks. In this paper …
Click prediction for web image reranking using multimodal sparse coding
Image reranking is effective for improving the performance of a text-based image search.
However, existing reranking algorithms are limited for two main reasons: 1) the textual meta …
However, existing reranking algorithms are limited for two main reasons: 1) the textual meta …
Unsupervised feature selection using nonnegative spectral analysis
In this paper, a new unsupervised learning algorithm, namely Nonnegative Discriminative
Feature Selection (NDFS), is proposed. To exploit the discriminative information in …
Feature Selection (NDFS), is proposed. To exploit the discriminative information in …
3-D object retrieval and recognition with hypergraph analysis
View-based 3-D object retrieval and recognition has become popular in practice, eg, in
computer aided design. It is difficult to precisely estimate the distance between two objects …
computer aided design. It is difficult to precisely estimate the distance between two objects …
Visual-textual joint relevance learning for tag-based social image search
Due to the popularity of social media websites, extensive research efforts have been
dedicated to tag-based social image search. Both visual information and tags have been …
dedicated to tag-based social image search. Both visual information and tags have been …