Mahesh Kumar Krishna Reddy

I have completed my M.Sc. in Computer Science at the University of Manitoba, where I was advised by Prof. Yang Wang. Previously, I received my B.E. in Information Science from Visvesvaraya Technological University, India.

Email: kumarkm {at} cs [dot] umanitoba [dot] ca

More about me:  

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News
New!July 2020: 1 paper accepted to BMVC 2020
New!July 2020: 2 papers accepted to ECCV 2020
New! May 2020: Started summer internship at Borealis AI
New! Apr. 2020: Successfully defended my M.Sc. thesis
Dec. 2019: 1 paper accepted to WACV 2020
Oct. 2019: Student Volunteer NeurIPS 2019
July 2019: 1 paper accepted to BMVC 2019
July 2019: 1 paper accepted to AVSS 2019

Publications
Sentence Guided Temporal Modulation for Dynamic Video Thumbnail Generation
Mrigank Rochan, Mahesh Kumar Krishna Reddy and Yang Wang

British Machine Vision Conference (BMVC), 2020

Adaptive Video Highlight Detection by Learning from User History
Mrigank Rochan, Mahesh Kumar Krishna Reddy, Linwei Ye and Yang Wang

European Conference on Computer Vision (ECCV), 2020

Few-Shot Scene-Adaptive Anomaly Detection
Yiwei Lu, Frank Yu, Mahesh Kumar Krishna Reddy and Yang Wang

European Conference on Computer Vision (ECCV), 2020 (Spotlight)

Few-Shot Scene Adaptive Crowd Counting Using Meta-Learning
Mahesh Kumar Krishna Reddy, Mohammad Asiful Hossain, Mrigank Rochan and Yang Wang

IEEE Winter Conference of Applications on Computer Vision (WACV), 2020

Domain Adaptation in Crowd Counting
Mohammad Asiful Hossain, Mahesh Kumar Krishna Reddy, Kevin Cannons, Zhan Xu and Yang Wang

Conference on Robot and Computer Vision (CRV), 2020

One-Shot Scene-Specific Crowd Counting
Mohammad Asiful Hossain, Mahesh Kumar Krishna Reddy, Mehrdad Hosseinzadeh, Omit Chanda and Yang Wang

British Machine Vision Conference (BMVC), 2019

Future Frame Prediction Using Convolutional VRNN for Anomaly Detection
Yiwei Lu, Mahesh Kumar Krishna Reddy, Seyed shahabeddin Nabavi and Yang Wang

IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS), 2019


Thesis

Credits to Jon Barron for the website design.