Xiaolong Wang

PhD, Carnegie Mellon University [GitHub] [Google Scholar]
Home Publication CV Contact

Xiaolong Wang*, Allan Jabri* and Alexei A. Efros.
Learning Correspondence from the Cycle-consistency of Time.
Conference on Computer Vision and Pattern Recognition (CVPR), 2019.(Oral Presentation.)
(*indicates equal contributions.)

[project page] [slides] [result video] [oral talk]
[arXiv] [BibTeX] [code]

Xueting Li, Sifei Liu, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, and Jan Kautz.
Putting Humans in a Scene: Learning Affordance in 3D Indoor Environments.
Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

[arXiv] [BibTeX]

Wei Yang, Xiaolong Wang, Ali Farhadi, Abhinav Gupta and Roozbeh Mottaghi.
Visual Semantic Navigation using Scene Priors.
International Conference on Machine Learning (ICLR), 2019.

[arXiv] [video] [BibTeX]

Xiaolong Wang and Abhinav Gupta.
Videos as Space-Time Region Graphs.
European Conference on Computer Vision (ECCV), 2018.

[arXiv] [BibTeX]

Tian Ye, Xiaolong Wang, James Davidson, and Abhinav Gupta.
Interpretable Intuitive Physics Model.
European Conference on Computer Vision (ECCV), 2018.

[pdf] [BibTeX] [code] [techxplore]

Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He.
Non-local Neural Networks.
Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

[arXiv] [BibTeX] [code]

Xiaolong Wang*, Yufei Ye*, and Abhinav Gupta.
Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs.
Conference on Computer Vision and Pattern Recognition (CVPR), 2018. (*indicates equal contributions.)

[arXiv] [BibTeX] [code]

Wei Yang , Wanli Ouyang, Xiaolong Wang, Jimmy Ren, Hongsheng Li and Xiaogang Wang.
3D Human Pose Estimation in the Wild by Adversarial Learning.
Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

[arXiv] [BibTeX]

Xiaolong Wang, Kaiming He, and Abhinav Gupta.
Transitive Invariance for Self-supervised Visual Representation Learning.
International Conference on Computer Vision (ICCV), 2017

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

Yuan Yuan, Xiaodan Liang, Xiaolong Wang, Dit-Yan Yeung, and Abhinav Gupta.
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection.
International Conference on Computer Vision (ICCV), 2017

[pdf] [BibTeX] [dataset]

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

[pdf] [BibTeX] [dataset] [project page] [spotlight video]

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

[pdf] [BibTeX] [code]

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

[pdf] [BibTeX] [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.
European Conference on Computer Vision (ECCV), 2016

[pdf] [BibTeX] [dataset]

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

[pdf] [BibTeX] [dataset]

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

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

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

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

David F. Fouhey, Xiaolong Wang, and Abhinav Gupta.
In Defense of the Direct Perception of Affordances.
arXiv, 2015.

[pdf]

Xiaolong Wang, Liliang Zhang, Liang Lin, Zhujin Liang, and Wangmeng Zuo.
Deep Joint Task Learning for Generic Object Extraction.
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.
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.
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.
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.
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.
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.
International Conference on Image Processing (ICIP), 2011.

[pdf]