activity
20182022
most citedCrowd Transformer Network

6 citations · 7 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

Exemplar Free Class Agnostic Counting

Viresh Ranjan, Minh Hoai

We tackle the task of Class Agnostic Counting, which aims to count objects in a novel object category at test time without any access to labeled training data for that category. Al…

cs.CV2021

Learning To Count Everything

Viresh Ranjan, Udbhav Sharma, Thu Nguyen +1

Existing works on visual counting primarily focus on one specific category at a time, such as people, animals, and cells. In this paper, we are interested in counting everything, t…

cs.CV2020

Uncertainty Estimation and Sample Selection for Crowd Counting

Viresh Ranjan, Boyu Wang, Mubarak Shah +1

We present a method for image-based crowd counting, one that can predict a crowd density map together with the uncertainty values pertaining to the predicted density map. To obtain…

cs.CV2020

A Study of Human Gaze Behavior During Visual Crowd Counting

Raji Annadi, Yupei Chen, Viresh Ranjan +3

In this paper, we describe our study on how humans allocate their attention during visual crowd counting. Using an eye tracker, we collect gaze behavior of human participants who a…

cs.CV20196 cited

Crowd Transformer Network

Viresh Ranjan, Mubarak Shah, Minh Hoai Nguyen

In this paper, we tackle the problem of Crowd Counting, and present a crowd density estimation based approach for obtaining the crowd count. Most of the existing crowd counting app…

cs.CL2018

Fake Sentence Detection as a Training Task for Sentence Encoding

Viresh Ranjan, Heeyoung Kwon, Niranjan Balasubramanian +1

Sentence encoders are typically trained on language modeling tasks with large unlabeled datasets. While these encoders achieve state-of-the-art results on many sentence-level tasks…