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News
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[NEW] 07 / 2020: One paper on Unsupervised Domain Adaptation accepted in BMVC'20!
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[NEW] 03 / 2020: One paper accepted in CVPR'20 workshop!
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08 / 2018: Our paper on "Connecting Visual Experiences using Max-flow Network with Application to
Visual Localization" is out on arXiv!
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06 / 2018: Our paper on "Improving Multiclass Classification by Deep Networks using DAGSVM and Triplet Loss" has been accepted at Pattern Recognition Letters 2018!
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05 / 2018: Started my internship at Honda Research Institute, Mountain View
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08 / 2017: Started my M.S. at UC Merced
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Unsupervised Domain Adaptation for Spatio-Temporal Action Localization
Nakul Agarwal, Yi-Ting Chen, Behzad Dariush, Ming-Hsuan Yang
Proceedings of British Machine Vision Conference (BMVC), 2020
project
Short Version: VL3 Workshop, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
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SegRPN: Scale Aware Joint Object Detection and Semantic Segmentation
Nakul Agarwal, Wei-Chih Hung, Yi-Hsuan Tsai, Ming-Hsuan Yang
Manuscript, 2019
paper
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Improving Multiclass Classification by Deep Networks using DAGSVM and Triplet Loss
Nakul Agarwal, Vineeth N. Balasubramaniam, C. V. Jawahar
Pattern Recognition Letters, 2018
paper bibtex
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Connecting Visual Experiences using Max-flow Network with Application to Visual Localization
A.H. Abdul Hafez*, Nakul Agarwal*, C. V. Jawahar
arXiv, 2018
* equal contribution
paper bibtex
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Exploring Action Recognition without using Deep Learning
Nakul Agarwal, 2019
report
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Content Based Image Retrieval
Nakul Agarwal, 2018
report
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Simultaneous Localization and Mapping using Extended Kalmann Filter
Nakul Agarwal, Aditya Ranganath, 2017
report
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Software Engineering (CSE 120), UC Merced
Teaching Assistant (TA) with Chi Yan Leung
Fall 2017
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Computer Architecture (CSE 140), UC Merced
Teaching Assistant (TA) with Chi Yan Leung
Spring 2018
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Intro to Digital Image Processing (CSE 107), UC Merced
Teaching Assistant (TA) with Shawn Newsam
Fall 2018
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