76 citations · 89 across the 4 of their papers we have counts for
8 papers
Learning to Predict Visual Attributes in the Wild
Khoi Pham, Kushal Kafle, Zhe Lin +4
Visual attributes constitute a large portion of information contained in a scene. Objects can be described using a wide variety of attributes which portray their visual appearance…
On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law
Damien Teney, Kushal Kafle, Robik Shrestha +3
Out-of-distribution (OOD) testing is increasingly popular for evaluating a machine learning system's ability to generalize beyond the biases of a training set. OOD benchmarks are d…
Do We Need Fully Connected Output Layers in Convolutional Networks?
Zhongchao Qian, Tyler L. Hayes, Kushal Kafle +1
Traditionally, deep convolutional neural networks consist of a series of convolutional and pooling layers followed by one or more fully connected (FC) layers to perform the final c…
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…
Answering Questions about Data Visualizations using Efficient Bimodal Fusion
Kushal Kafle, Robik Shrestha, Brian Price +2
Chart question answering (CQA) is a newly proposed visual question answering (VQA) task where an algorithm must answer questions about data visualizations, e.g. bar charts, pie cha…
Challenges and Prospects in Vision and Language Research
Kushal Kafle, Robik Shrestha, Christopher Kanan
Language grounded image understanding tasks have often been proposed as a method for evaluating progress in artificial intelligence. Ideally, these tasks should test a plethora of…