activity
20162021
most citedTemporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification

187 citations · 221 across the 8 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CV20197 cited

ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations

Vivek Sharma, Praneeth Vepakomma, Tristan Swedish +3

Recently, there has been the development of Split Learning, a framework for distributed computation where model components are split between the client and server (Vepakomma et al.…

cs.LG20194 cited

ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries

Vivek Sharma, Praneeth Vepakomma, Tristan Swedish +3

In this work we introduce ExpertMatcher, a method for automating deep learning model selection using autoencoders. Specifically, we are interested in performing inference on data s…

cs.CV2019

DynamoNet: Dynamic Action and Motion Network

Ali Diba, Vivek Sharma, Luc Van Gool +1

In this paper, we are interested in self-supervised learning the motion cues in videos using dynamic motion filters for a better motion representation to finally boost human action…

cs.CV2019

Large Scale Holistic Video Understanding

Ali Diba, Mohsen Fayyaz, Vivek Sharma +4

Video recognition has been advanced in recent years by benchmarks with rich annotations. However, research is still mainly limited to human action or sports recognition - focusing…

cs.CV2019

Self-Supervised Learning of Face Representations for Video Face Clustering

Vivek Sharma, Makarand Tapaswi, M. Saquib Sarfraz +1

Analyzing the story behind TV series and movies often requires understanding who the characters are and what they are doing. With improving deep face models, this may seem like a s…

cs.CV201916 cited

Efficient Parameter-free Clustering Using First Neighbor Relations

M. Saquib Sarfraz, Vivek Sharma, Rainer Stiefelhagen

We present a new clustering method in the form of a single clustering equation that is able to directly discover groupings in the data. The main proposition is that the first neigh…