Search Results for author: Deepti Ghadiyaram

Found 15 papers, 10 papers with code

Mitigating stereotypical biases in text to image generative systems

no code implementations10 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.

Fairness

Helping Visually Impaired People Take Better Quality Pictures

1 code implementation14 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.

Multi-Task Learning

Telepresence Video Quality Assessment

no code implementations20 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.

Video Quality Assessment

Making Heads or Tails: Towards Semantically Consistent Visual Counterfactuals

1 code implementation24 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.

counterfactual Counterfactual Explanation +1

Generic Event Boundary Detection: A Benchmark for Event Segmentation

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.

Action Detection Boundary Detection +3

Patch-VQ: 'Patching Up' the Video Quality Problem

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)

Video Quality Assessment Visual Question Answering (VQA)

How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language

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.

Sign Language Production Sign Language Translation +1

From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Quality

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.

Blind Image Quality Assessment Video Quality Assessment

ClusterFit: Improving Generalization of Visual Representations

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.

Action Classification Clustering +2

Large-scale weakly-supervised pre-training for video action recognition

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)

Action Classification Action Recognition +3

Less is More: Learning Highlight Detection from Video Duration

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.

Highlight Detection

Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approach

1 code implementation15 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.

Massive Online Crowdsourced Study of Subjective and Objective Picture Quality

no code implementations9 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

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