224 citations · 2.3k across the 117 of their papers we have counts for
8 papers · 1 filter
An Unsupervised Game-Theoretic Approach to Saliency Detection
Yu Zeng, Huchuan Lu, Ali Borji +1
We propose a novel unsupervised game-theoretic salient object detection algorithm that does not require labeled training data. First, saliency detection problem is formulated as a…
Learning Uncertain Convolutional Features for Accurate Saliency Detection
Pingping Zhang, Dong Wang, Huchuan Lu +2
Deep convolutional neural networks (CNNs) have delivered superior performance in many computer vision tasks. In this paper, we propose a novel deep fully convolutional network mode…
Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection
Pingping Zhang, Dong Wang, Huchuan Lu +2
Fully convolutional neural networks (FCNs) have shown outstanding performance in many dense labeling problems. One key pillar of these successes is mining relevant information from…
Statistics of Deep Generated Images
Yu Zeng, Huchuan Lu, Ali Borji
Here, we explore the low-level statistics of images generated by state-of-the-art deep generative models. First, Variational auto-encoder (VAE~\cite{kingma2013auto}), Wasserstein g…
Learning Spatial-Aware Regressions for Visual Tracking
Chong Sun, Dong Wang, Huchuan Lu +1
In this paper, we analyze the spatial information of deep features, and propose two complementary regressions for robust visual tracking. First, we propose a kernelized ridge regre…
Deep Mutual Learning
Ying Zhang, Tao Xiang, Timothy M. Hospedales +1
Model distillation is an effective and widely used technique to transfer knowledge from a teacher to a student network. The typical application is to transfer from a powerful large…
Hierarchical Cellular Automata for Visual Saliency
Yao Qin, Mengyang Feng, Huchuan Lu +1
Saliency detection, finding the most important parts of an image, has become increasingly popular in computer vision. In this paper, we introduce Hierarchical Cellular Automata (HC…
Pose Invariant Embedding for Deep Person Re-identification
Liang Zheng, Yujia Huang, Huchuan Lu +1
Pedestrian misalignment, which mainly arises from detector errors and pose variations, is a critical problem for a robust person re-identification (re-ID) system. With bad alignmen…