no code implementations • 10 Oct 2023 • Piero Esposito, Parmida Atighehchian, Anastasis Germanidis, Deepti Ghadiyaram
In this work, we propose a method to mitigate such biases and ensure that the outcomes are fair across different groups of people.
1 code implementation • 14 May 2023 • Maniratnam Mandal, Deepti Ghadiyaram, Danna Gurari, Alan C. Bovik
The photographs taken by visually impaired users often suffer from one or both of two kinds of quality issues: technical quality (distortions), and semantic quality, such as framing and aesthetic composition.
no code implementations • 20 Jul 2022 • Zhenqiang Ying, Deepti Ghadiyaram, Alan Bovik
Video conferencing, which includes both video and audio content, has contributed to dramatic increases in Internet traffic, as the COVID-19 pandemic forced millions of people to work and learn from home.
1 code implementation • 24 Mar 2022 • Simon Vandenhende, Dhruv Mahajan, Filip Radenovic, Deepti Ghadiyaram
A visual counterfactual explanation replaces image regions in a query image with regions from a distractor image such that the system's decision on the transformed image changes to the distractor class.
2 code implementations • ICCV 2021 • Mike Zheng Shou, Stan Weixian Lei, Weiyao Wang, Deepti Ghadiyaram, Matt Feiszli
This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks.
1 code implementation • CVPR 2021 • Zhenqiang Ying, Maniratnam Mandal, Deepti Ghadiyaram, Alan Bovik
No-reference (NR) perceptual video quality assessment (VQA) is a complex, unsolved, and important problem to social and streaming media applications.
Ranked #10 on Video Quality Assessment on LIVE-FB LSVQ (using extra training data)
1 code implementation • CVPR 2021 • Amanda Duarte, Shruti Palaskar, Lucas Ventura, Deepti Ghadiyaram, Kenneth DeHaan, Florian Metze, Jordi Torres, Xavier Giro-i-Nieto
Towards this end, we introduce How2Sign, a multimodal and multiview continuous American Sign Language (ASL) dataset, consisting of a parallel corpus of more than 80 hours of sign language videos and a set of corresponding modalities including speech, English transcripts, and depth.
1 code implementation • CVPR 2020 • Krishna Kumar Singh, Dhruv Mahajan, Kristen Grauman, Yong Jae Lee, Matt Feiszli, Deepti Ghadiyaram
Our key idea is to decorrelate feature representations of a category from its co-occurring context.
2 code implementations • CVPR 2020 • Zhenqiang Ying, Haoran Niu, Praful Gupta, Dhruv Mahajan, Deepti Ghadiyaram, Alan Bovik
Blind or no-reference (NR) perceptual picture quality prediction is a difficult, unsolved problem of great consequence to the social and streaming media industries that impacts billions of viewers daily.
Ranked #4 on Video Quality Assessment on MSU SR-QA Dataset
1 code implementation • CVPR 2020 • Xueting Yan, Ishan Misra, Abhinav Gupta, Deepti Ghadiyaram, Dhruv Mahajan
Pre-training convolutional neural networks with weakly-supervised and self-supervised strategies is becoming increasingly popular for several computer vision tasks.
Ranked #53 on Image Classification on iNaturalist 2018
3 code implementations • CVPR 2019 • Deepti Ghadiyaram, Matt Feiszli, Du Tran, Xueting Yan, Heng Wang, Dhruv Mahajan
Second, frame-based models perform quite well on action recognition; is pre-training for good image features sufficient or is pre-training for spatio-temporal features valuable for optimal transfer learning?
Ranked #2 on Egocentric Activity Recognition on EPIC-KITCHENS-55 (Actions Top-1 (S2) metric)
no code implementations • CVPR 2019 • Zhenheng Yang, Dhruv Mahajan, Deepti Ghadiyaram, Ram Nevatia, Vignesh Ramanathan
Weakly supervised object detection aims at reducing the amount of supervision required to train detection models.
Ranked #1 on Weakly Supervised Object Detection on Charades
no code implementations • CVPR 2019 • Bo Xiong, Yannis Kalantidis, Deepti Ghadiyaram, Kristen Grauman
Highlight detection has the potential to significantly ease video browsing, but existing methods often suffer from expensive supervision requirements, where human viewers must manually identify highlights in training videos.
1 code implementation • 15 Sep 2016 • Deepti Ghadiyaram, Alan C. Bovik
Current top-performing blind perceptual image quality prediction models are generally trained on legacy databases of human quality opinion scores on synthetically distorted images.
no code implementations • 9 Nov 2015 • Deepti Ghadiyaram, Alan C. Bovik
Towards overcoming these limitations, we designed and created a new database that we call the LIVE In the Wild Image Quality Challenge Database, which contains widely diverse authentic image distortions on a large number of images captured using a representative variety of modern mobile devices.
Blind Image Quality Assessment Small Data Image Classification