activity
20172023
most citedRegularize, Expand and Compress: Multi-task based Lifelong Learning via NonExpansive AutoML

3 citations · 3 across the 4 of their papers we have counts for

collaborators

9 papers

cs.MM2023

Just Noticeable Difference-aware Per-Scene Bitrate-laddering for Adaptive Video Streaming

Vignesh V Menon, Jingwen Zhu, Prajit T Rajendran +3

In video streaming applications, a fixed set of bitrate-resolution pairs (known as a bitrate ladder) is typically used during the entire streaming session. However, an optimized bi…

eess.IV2022

On the benefit of parameter-driven approaches for the modeling and the prediction of Satisfied User Ratio for compressed video

Jingwen Zhu, Patrick Le Callet, Anne-Flore Perrin +2

The human eye cannot perceive small pixel changes in images or videos until a certain threshold of distortion. In the context of video compression, Just Noticeable Difference (JND)…

eess.IV2022

A Framework to Map VMAF with the Probability of Just Noticeable Difference between Video Encoding Recipes

Jingwen Zhu, Suiyi Ling, Yoann Baveye +1

Just Noticeable Difference (JND) model developed based on Human Vision System (HVS) through subjective studies is valuable for many multimedia use cases. In the streaming industrie…

cs.CV2020

Few-Shot Object Detection in Real Life: Case Study on Auto-Harvest

Kevin Riou, Jingwen Zhu, Suiyi Ling +3

Confinement during COVID-19 has caused serious effects on agriculture all over the world. As one of the efficient solutions, mechanical harvest/auto-harvest that is based on object…

cs.CV2019

Accelerating Proposal Generation Network for \\Fast Face Detection on Mobile Devices

Heming Zhang, Xiaolong Wang, Jingwen Zhu +1

Face detection is a widely studied problem over the past few decades. Recently, significant improvements have been achieved via the deep neural network, however, it is still challe…

cs.CV2019

RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge

Dawei Li, Serafettin Tasci, Shalini Ghosh +3

Object detection models shipped with camera-equipped edge devices cannot cover the objects of interest for every user. Therefore, the incremental learning capability is a critical…