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cs.CV2026

PinPoint: Evaluation of Composed Image Retrieval with Explicit Negatives, Multi-Image Queries, and Paraphrase Testing

Rohan Mahadev, Joyce Yuan, Patrick Poirson +3

Composed Image Retrieval (CIR) has made significant progress, yet current benchmarks are limited to single ground-truth answers and lack the annotations needed to evaluate false po…

cs.CV2025

Visual Product Graph: Bridging Visual Products And Composite Images For End-to-End Style Recommendations

Yue Li Du, Ben Alexander, Mikhail Antonenka +3

Retrieving semantically similar but visually distinct contents has been a critical capability in visual search systems. In this work, we aim to tackle this problem with Visual Prod…

cs.CV2021

Understanding Gender and Racial Disparities in Image Recognition Models

Rohan Mahadev, Anindya Chakravarti

Large scale image classification models trained on top of popular datasets such as Imagenet have shown to have a distributional skew which leads to disparities in prediction accura…

cs.CV2019

Improving Visual Recognition using Ambient Sound for Supervision

Rohan Mahadev, Hongyu Lu

Our brains combine vision and hearing to create a more elaborate interpretation of the world. When the visual input is insufficient, a rich panoply of sounds can be used to describ…

cs.CV2019

Demystifying Multi-Faceted Video Summarization: Tradeoff Between Diversity,Representation, Coverage and Importance

Vishal Kaushal, Rishabh Iyer, Khoshrav Doctor +6

This paper addresses automatic summarization of videos in a unified manner. In particular, we propose a framework for multi-faceted summarization for extractive, query base and ent…

cs.CV2019

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision

Vishal Kaushal, Rishabh Iyer, Suraj Kothawade +3

Supervised machine learning based state-of-the-art computer vision techniques are in general data hungry. Their data curation poses the challenges of expensive human labeling, inad…