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20162026
most citedLightweight Compression of Intermediate Neural Network Features for Collaborative Intelligence

32 citations · 56 across the 12 of their papers we have counts for

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7 papers · 1 filter

eess.IV2024

Privacy-Preserving Autoencoder for Collaborative Object Detection

Bardia Azizian, Ivan V. Bajic

Privacy is a crucial concern in collaborative machine vision where a part of a Deep Neural network (DNN) model runs on the edge, and the rest is executed on the cloud. In such appl…

eess.IV20232 cited

VVC+M: Plug and Play Scalable Image Coding for Humans and Machines

Alon Harell, Yalda Foroutan, Ivan V. Bajic

Compression for machines is an emerging field, where inputs are encoded while optimizing the performance of downstream automated analysis. In scalable coding for humans and machine…

eess.IV2023

Rate-Distortion Theory in Coding for Machines and its Application

Alon Harell, Yalda Foroutan, Nilesh Ahuja +6

Recent years have seen a tremendous growth in both the capability and popularity of automatic machine analysis of images and video. As a result, a growing need for efficient compre…

eess.IV2021

Latent-space scalability for multi-task collaborative intelligence

Hyomin Choi, Ivan V. Bajic

We investigate latent-space scalability for multi-task collaborative intelligence, where one of the tasks is object detection and the other is input reconstruction. In our proposed…

eess.IV2020

Affine Transformation-Based Deep Frame Prediction

Hyomin Choi, Ivan V. Bajić

We propose a neural network model to estimate the current frame from two reference frames, using affine transformation and adaptive spatially-varying filters. The estimated affine…

eess.IV2019

Deep Frame Prediction for Video Coding

Hyomin Choi, Ivan V. Bajic

We propose a novel frame prediction method using a deep neural network (DNN), with the goal of improving video coding efficiency. The proposed DNN makes use of decoded frames, at b…