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Salient Object Detection via High-to-Low Hierarchical Context Aggregation
Yun Liu, Yu Qiu, Le Zhang +3
Recent progress on salient object detection mainly aims at exploiting how to effectively integrate convolutional side-output features in convolutional neural networks (CNN). Based…
CubemapSLAM: A Piecewise-Pinhole Monocular Fisheye SLAM System
Yahui Wang, Shaojun Cai, Shi-Jie Li +4
We present a real-time feature-based SLAM (Simultaneous Localization and Mapping) system for fisheye cameras featured by a large field-of-view (FoV). Large FoV cameras are benefici…
Self-Erasing Network for Integral Object Attention
Qibin Hou, Peng-Tao Jiang, Yunchao Wei +1
Recently, adversarial erasing for weakly-supervised object attention has been deeply studied due to its capability in localizing integral object regions. However, such a strategy r…
MatchBench: An Evaluation of Feature Matchers
JiaWang Bian, Ruihan Yang, Yun Liu +4
Feature matching is one of the most fundamental and active research areas in computer vision. A comprehensive evaluation of feature matchers is necessary, since it would advance bo…
Learning Pixel-wise Labeling from the Internet without Human Interaction
Yun Liu, Yujun Shi, JiaWang Bian +3
Deep learning stands at the forefront in many computer vision tasks. However, deep neural networks are usually data-hungry and require a huge amount of well-annotated training samp…
Enhanced-alignment Measure for Binary Foreground Map Evaluation
Deng-Ping Fan, Cheng Gong, Yang Cao +3
The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways. These measures consider pixel-level match or image-leve…