Mrigank Rochan

Email: mrochan@cs.umanitoba.ca
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About Me

I received the Ph.D. degree in Computer Science from the University of Manitoba in 2020, where I was advised by Prof. Yang Wang. I received an M.Sc. degree in Computer Science from the University of Manitoba in 2016 and the B.Tech. degree in Computer Science and Engineering from Amrita University, India, in 2011. I was a visiting research student at Simon Fraser University in 2015-2016. I also did a research internship at Mapillary (acquired by Facebook) in 2018-2019.

My research is focused on Deep Learning and its applications in Computer Vision.

News

^NEW 07/2021: One paper accepted to ICCV 2021!
^NEW 05/2021: Received the CIPPRS John Barron Doctoral Dissertation Award for 2020. See announcement here!
^NEW 01/2021: 1 paper accepted to IEEE TPAMI!
10/2020: I gave a talk on Video Abstraction at the University of Guelph!
10/2020: I gave a talk on Video Abstraction at the Vector Institute!
08/2020: Successfully defended my Ph.D. thesis!
07/2020: One paper accepted to ECCV 2020!
07/2020: One paper accepted to BMVC 2020!
10/2019: NeurIPS 2019 Travel Award!
09/2019: Program committee member of Workshop on Multi-modal Video Analysis at ICCV 2019!
03/2019: Two papers accepted to CVPR 2019!
03/2019: One paper accepted to ICME 2019!
07/2018: One paper accepted to ECCV 2018!

Selected Publications

	Joint Visual and Audio Learning for Video Highlight Detection Taivanbat Badamdorj, Mrigank Rochan, Yang Wang, and Li Cheng IEEE/CVF International Conference on Computer Vision (ICCV), 2021. [paper]
	Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network Linwei Ye, Mrigank Rochan, Zhi Liu, Xiaoqin Zhang, and Yang Wang IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021. [arXiv] [code]
	AdaCrowd: Unlabeled Scene Adaptation for Crowd Counting Mahesh Kumar, Mrigank Rochan, Yiwei Lu, and Yang Wang IEEE Transactions on Multimedia (TMM), 2021. [arXiv] [code]
	Efficient Deep Learning Models for Video Abstraction Mrigank Rochan Ph.D. Thesis, University of Manitoba, 2020. CIPPRS John Barron Doctoral Dissertation Award 2020 [link]
	Adaptive Video Highlight Detection by Learning from User History Mrigank Rochan, Mahesh Kumar, Linwei Ye, and Yang Wang European Conference on Computer Vision (ECCV), 2020. [arXiv] [code]
	Sentence Guided Temporal Modulation for Dynamic Video Thumbnail Generation Mrigank Rochan, Mahesh Kumar, and Yang Wang British Machine Vision Conference (BMVC), 2020. [arXiv]
	Few-Shot Scene Adaptive Crowd Counting Using Meta-Learning Mahesh Kumar, Md Hossain, Mrigank Rochan and Yang Wang IEEE Winter Conference of Applications on Computer Vision (WACV), 2020. [arXiv] [code]
	Video Summarization by Learning from Unpaired Data Mrigank Rochan and Yang Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [arXiv]
	Cross-Modal Self-Attention Network for Referring Image Segmentation Linwei Ye, Mrigank Rochan, Zhi Liu, and Yang Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [arXiv] [code]
	Convolutional Temporal Attention Model for Video-based Person Re-identification Tanzila Rahman, Mrigank Rochan, and Yang Wang IEEE International Conference on Multimedia and Expo (ICME), 2019. [arXiv]
	Video Summarization Using Fully Convolutional Sequence Networks Mrigank Rochan, Linwei Ye, and Yang Wang European Conference on Computer Vision (ECCV), 2018. [paper] [arXiv]
	Future Semantic Segmentation with Convolutional LSTM Seyed Nabavi, Mrigank Rochan, and Yang Wang British Machine Vision Conference (BMVC), 2018. [arXiv]
	Gated Feedback Refinement Network for Dense Image Labeling Md Amirul Islam, Mrigank Rochan, Neil Bruce, and Yang Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [paper] [extended version] [code]
	Person Re-Identification by Localizing Discriminative Regions Tanzila Rahman, Mrigank Rochan, and Yang Wang British Machine Vision Conference (BMVC), 2017. [paper]
	Adapting Object Detectors from Images to Weakly Labeled Videos Omit Chanda, Eu Wern Teh, Mrigank Rochan, Zhenyu Guo, and Yang Wang British Machine Vision Conference (BMVC), 2017. [paper] [code]
	Salient Object Detection using a Context-Aware Refinement Network Md Amirul Islam, Mahmoud Kalash, Mrigank Rochan, Neil Bruce, and Yang Wang British Machine Vision Conference (BMVC), 2017. [paper]
	Label Refinement Network for Coarse-to-Fine Semantic Segmentation Md Amirul Islam, Shujon Naha, Mrigank Rochan, Neil Bruce, and Yang Wang arXiv preprint arXiv:1606.07415, 2017. [arXiv]
	Attention Networks for Weakly Supervised Object Localization Eu Wern Teh, Mrigank Rochan, and Yang Wang British Machine Vision Conference (BMVC), 2016. [paper]
	Object Localization in Weakly Labeled Images and Videos Mrigank Rochan M.Sc. Thesis, University of Manitoba, 2016. [link]
	Weakly Supervised Object Localization and Segmentation in Videos Mrigank Rochan and Yang Wang Image and Vision Computing (IVC), 2016. [paper]
	Weakly Supervised Localization of Novel Objects using Appearance Transfer Mrigank Rochan and Yang Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [paper]
	Latent SVM for Object Localization in Weakly Labeled Videos Mrigank Rochan and Yang Wang Canadian Conference on Computer and Robot Vision (CRV), 2015. [paper]
	Efficient Object Localization and Segmentation in Weakly Labeled Videos Mrigank Rochan and Yang Wang International Symposium on Visual Computing (ISVC), 2014. Oral Presentation [paper]
	Segmenting Objects in Weakly Labeled Videos Mrigank Rochan, Shafin Rahman, Neil Bruce, and Yang Wang Canadian Conference on Computer and Robot Vision (CRV), 2014. Oral Presentation [paper] [demo video]
	Examining Visual Saliency Prediction in Naturalistic Scenes Shafin Rahman, Mrigank Rochan, Yang Wang, and Neil Bruce IEEE International Conference on Image Processing (ICIP), 2014. Oral Presentation [paper]
	See Google Scholar for full publication list