no code implementations • 3 Aug 2020 • Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, Ming-Hsuan Yang
Obtaining object response maps is one important step to achieve weakly-supervised semantic segmentation using image-level labels.
1 code implementation • CVPR 2020 • Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, Ming-Hsuan Yang
Existing weakly-supervised semantic segmentation methods using image-level annotations typically rely on initial responses to locate object regions.
1 code implementation • 18 Dec 2018 • Muratcan Cicek, Jinrong Xie, Qiaosong Wang, Robinson Piramuthu
Unlike desktop and laptop computers, they are also much easier to carry indoors and outdoors. To address this, we implement and open source button that is sensitive to head movements tracked from the front camera of iPhone X.
Human-Computer Interaction
no code implementations • 6 Jul 2018 • Kevin Lin, Fan Yang, Qiaosong Wang, Robinson Piramuthu
Fine-grained image search is still a challenging problem due to the difficulty in capturing subtle differences regardless of pose variations of objects from fine-grained categories.
no code implementations • 31 Jul 2017 • Mahyar Najibi, Fan Yang, Qiaosong Wang, Robinson Piramuthu
In this work, we propose an efficient and effective approach for unconstrained salient object detection in images using deep convolutional neural networks.
no code implementations • 10 Jun 2017 • Fan Yang, Ajinkya Kale, Yury Bubnov, Leon Stein, Qiaosong Wang, Hadi Kiapour, Robinson Piramuthu
We harness the availability of large image collection of eBay listings and state-of-the-art deep learning techniques to perform visual search at scale.
no code implementations • CVPR 2016 • Qiaosong Wang, Wen Zheng, Robinson Piramuthu
We propose an unsupervised bottom-up saliency detection approach by exploiting novel graph structure and background priors.
no code implementations • 15 Jun 2015 • Qiaosong Wang, Haiting Lin, Yi Ma, Sing Bing Kang, Jingyi Yu
We propose a novel approach that jointly removes reflection or translucent layer from a scene and estimates scene depth.
no code implementations • 3 Oct 2014 • Qiaosong Wang, Vignesh Jagadeesh, Bryan Ressler, Robinson Piramuthu
In this paper, we propose a method for capturing accurate human body shape and anthropometrics from a single consumer grade depth sensor.