Manoj Acharya

Manoj Acharya

PhD Student, Rochester Institute of Technology


Research Interests

I am a PhD student in the Imaging Science department at the Rochester Institute of Technology in Rochester, NY. I am working with my adviser Dr. Christopher Kanan on machine learning algorithms mostly in the intersection of language and vision. My overall goal is to develop multimodal systems that can leverage large amounts of data in a semi-supervised or fully unsupervised manner.
Besides my main research, I am also interested in seeing how ML technology in general can be effectively used for serving poeple in developing and underdeveloped countries. I am also looking forward to collaborate with people from diverse backgrounds and share ideas on how AI in general can be used for more good.

Timeline Events

April 2022:Our paper "Detecting out-of-context objects using graph contextual reasoning network" is accepted to IJCAI-ECAI 2022 !!
Oct 2021: Secured second position in the SODA10M Continual Object Detection Challenge at ICCV 2021 !!
Sep 2021: Spent three months working as a Summer Research Intern at SRI International.
April 2021: I successfully defended my dissertation proposal and advanced to candidacy.
Jul 2020: Our paper "RODEO: Replay for Online Object Detection" is accepted to BMVC 2020!!
Jul 2020: Our paper "REMIND Your Neural Network to Prevent Catastrophic Forgetting" is accepted to ECCV 2020! (27.1% acceptance rate)
Oct 2019: Our work got featured in RIT news!!
Sep 2019: We won the Facebook Eye Tracking Semantic Segmentation Challenge!!
Feb 2019: Our short paper is accepted to NAACL 2019!!
Nov 2018: TallyQA won the best poster award in the annual RIT Graduate Showcase!!
Nov 2018: Our paper is accepted to AAAI 2019. (acceptance rate ~16%)
July 2017: Started working at Klab under Dr. Christopher Kanan.
July 2017: Passed the Imaging science PhD qualifying exam.


Detecting out-of-context objects using graph contextual reasoning network.
Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran
abstract / bibtex / code

2nd Place Solution for SODA10M Challenge 2021 -- Continual Detection Track.
Manoj Acharya, and Christopher Kanan
ICCVW 2021
abstract / bibtex /

RODEO: Replay for Online Object Detection.
Manoj Acharya, Tyler L. Hayes, and Christopher Kanan
BMVC 2020
abstract / bibtex / code / video

REMIND Your Neural Network to Prevent Catastrophic Forgetting.
Tyler L. Hayes*, Kushal Kafle*, Robik Shrestha*, Manoj Acharya, and Christopher Kanan
ECCV 2020
abstract / bibtex / code

RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking.
Aayush Chaudhary*, Rakshit Kothari*,Manoj Acharya*, Shusil Dangi, Nitinraj Nair, Reynold Bailey, Christopher Kanan ,Gabriel Diaz, Jeff Pelz
ICCVW 2019 (Competition Winner)
abstract / bibtex / code

VQD: Visual Query Detection in Natural Scenes.
Manoj Acharya , Karan Jariwala, Christopher Kanan
NAACL 2019
abstract / bibtex / website

TallyQA: Answering Complex Counting Questions.
Manoj Acharya , Kushal Kafle, Christopher Kanan
AAAI 2019 (Spotlight Presentation)
abstract / bibtex / website / code