Search Results for author: Evgenya Pergament

Found 6 papers, 1 papers with code

PIM: Video Coding using Perceptual Importance Maps

no code implementations20 Dec 2022 Evgenya Pergament, Pulkit Tandon, Oren Rippel, Lubomir Bourdev, Alexander G. Anderson, Bruno Olshausen, Tsachy Weissman, Sachin Katti, Kedar Tatwawadi

The contributions of this work are threefold: (1) we introduce a web-tool which allows scalable collection of fine-grained perceptual importance, by having users interactively paint spatio-temporal maps over encoded videos; (2) we use this tool to collect a dataset with 178 videos with a total of 14443 frames of human annotated spatio-temporal importance maps over the videos; and (3) we use our curated dataset to train a lightweight machine learning model which can predict these spatio-temporal importance regions.

Video Compression

An Interactive Annotation Tool for Perceptual Video Compression

1 code implementation8 May 2022 Evgenya Pergament, Pulkit Tandon, Kedar Tatwawadi, Oren Rippel, Lubomir Bourdev, Bruno Olshausen, Tsachy Weissman, Sachin Katti, Alexander G. Anderson

We use this tool to collect data in-the-wild (10 videos, 17 users) and utilize the obtained importance maps in the context of x264 coding to demonstrate that the tool can indeed be used to generate videos which, at the same bitrate, look perceptually better through a subjective study - and are 1. 9 times more likely to be preferred by viewers.

Video Compression

ML-EXray: Visibility into ML Deployment on the Edge

no code implementations8 Nov 2021 Hang Qiu, Ioanna Vavelidou, Jian Li, Evgenya Pergament, Pete Warden, Sandeep Chinchali, Zain Asgar, Sachin Katti

The key challenge is that there is not much visibility into ML inference execution on edge devices, and very little awareness of potential issues during the edge deployment process.

Quantization

Sampling Training Data for Continual Learning Between Robots and the Cloud

no code implementations12 Dec 2020 Sandeep Chinchali, Evgenya Pergament, Manabu Nakanoya, Eyal Cidon, Edward Zhang, Dinesh Bharadia, Marco Pavone, Sachin Katti

Today's robotic fleets are increasingly measuring high-volume video and LIDAR sensory streams, which can be mined for valuable training data, such as rare scenes of road construction sites, to steadily improve robotic perception models.

Cloud Computing Continual Learning +2

Characterizing and Taming Model Instability Across Edge Devices

no code implementations18 Oct 2020 Eyal Cidon, Evgenya Pergament, Zain Asgar, Asaf Cidon, Sachin Katti

We characterize different sources for instability, and show that differences in compression formats and image signal processing account for significant instability in object classification models.

Network Offloading Policies for Cloud Robotics: a Learning-based Approach

no code implementations15 Feb 2019 Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone

In this paper, we formulate a novel Robot Offloading Problem --- how and when should robots offload sensing tasks, especially if they are uncertain, to improve accuracy while minimizing the cost of cloud communication?

Decision Making object-detection +1

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