Xiaolong Wang

PhD student, Carnegie Mellon University [GitHub] [Google Scholar]
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Xiaolong Wang, Kaiming He, and Abhinav Gupta. Transitive Invariance for Self-supervised Visual Representation Learning Proc. of IEEE International Conference on Computer Vision (ICCV), 2017

[pdf] [caffe_model(RGB order input)] [caffe_prototxt]

Xiaolong Wang*, Rohit Girdhar*, and Abhinav Gupta. Binge Watching: Scaling Affordance Learning from Sitcoms. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (spotlight presentation) (*indicates equal contributions.)

[pdf]

[code and data coming soon!]

Xiaolong Wang, Abhinav Shrivastava, and Abhinav Gupta. A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017

[pdf] [code]

Xiaolong Wang and Abhinav Gupta. Generative Image Modeling using Style and Structure Adversarial Networks. Proc. of European Conference on Computer Vision (ECCV), 2016

[pdf] [code] [models and dataset]

Gunnar A. Sigurdsson, Gül Varol, Xiaolong Wang, Ivan Laptev, Ali Farhadi, Abhinav Gupta. Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding. Proc. of European Conference on Computer Vision (ECCV), 2016

[pdf] [dataset]

Xiaolong Wang, Ali Farhadi, and Abhinav Gupta. Actions ~ Transformations. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016

[pdf] [BibTeX] [dataset]

Xiaolong Wang and Abhinav Gupta. Unsupervised Learning of Visual Representations using Videos. Proc. of IEEE International Conference on Computer Vision (ICCV), 2015

[pdf] [code] [model] [mined_patches] [project page] [spotlight video]

Xiaolong Wang, David F. Fouhey, and Abhinav Gupta. Designing Deep Networks for Surface Normal Estimation. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.

[pdf] [results for NYU Depth V2] [code and models] [project page]

Xiaolong Wang, Liliang Zhang, Liang Lin, Zhujin Liang, and Wangmeng Zuo. Deep Joint Task Learning for Generic Object Extraction. Proc. of Advances in Neural Information Processing Systems (NIPS), 2014.

[pdf] [dataset] [test code] [results]

Keze Wang, Xiaolong Wang, and Liang Lin. Deep Structured Models for 3D Human Activity Recognition. Proc. of ACM International Conference on Multimedia (MM), 2014. (full paper, oral presentation)

[pdf]

Zhujin Liang, Xiaolong Wang, Rui Huang, and Liang Lin. An Expressive Deep Model for Parsing Human Action from a Single Image. Proc. of IEEE International Conference on Multimedia and Expo (ICME), 2014. (oral presentation, Best Student Paper Award)

[pdf]

Xiaolong Wang, Liang Lin, and Lichao Huang, Shuicheng Yan. Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.

[pdf]

Xiaolong Wang and Liang Lin. Dynamical And-Or Graph Learning for Object Shape Modeling and Detection. Proc. of Advances in Neural Information Processing Systems (NIPS), 2012.

[pdf]

Liang Lin, Xiaolong Wang, Wei Yang, and Jian-Huang Lai. Learning Contour-Fragment-based Shape Model with And-Or Tree Representation. Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.

[pdf]

Wei Yang, Xiaolong Wang, Liang Lin, Chengying Gao. Interactive CT image segmentation with online discriminative learning. Proc. of IEEE International Conference on Image Processing (ICIP), 2011.

[pdf]