27 citations · 39 across the 3 of their papers we have counts for
6 papers
Detecting out-of-context objects using contextual cues
Manoj Acharya, Anirban Roy, Kaushik Koneripalli +3
This paper presents an approach to detect out-of-context (OOC) objects in an image. Given an image with a set of objects, our goal is to determine if an object is inconsistent with…
RODEO: Replay for Online Object Detection
Manoj Acharya, Tyler L. Hayes, Christopher Kanan
Humans can incrementally learn to do new visual detection tasks, which is a huge challenge for today's computer vision systems. Incrementally trained deep learning models lack back…
REMIND Your Neural Network to Prevent Catastrophic Forgetting
Tyler L. Hayes, Kushal Kafle, Robik Shrestha +2
People learn throughout life. However, incrementally updating conventional neural networks leads to catastrophic forgetting. A common remedy is replay, which is inspired by how the…
RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking
Aayush K. Chaudhary, Rakshit Kothari, Manoj Acharya +6
Accurate eye segmentation can improve eye-gaze estimation and support interactive computing based on visual attention; however, existing eye segmentation methods suffer from issues…
VQD: Visual Query Detection in Natural Scenes
Manoj Acharya, Karan Jariwala, Christopher Kanan
We propose Visual Query Detection (VQD), a new visual grounding task. In VQD, a system is guided by natural language to localize a variable number of objects in an image. VQD is re…
TallyQA: Answering Complex Counting Questions
Manoj Acharya, Kushal Kafle, Christopher Kanan
Most counting questions in visual question answering (VQA) datasets are simple and require no more than object detection. Here, we study algorithms for complex counting questions t…