86 citations · 543 across the 30 of their papers we have counts for
9 papers · 1 filter
Unbiasing Semantic Segmentation For Robot Perception using Synthetic Data Feature Transfer
Jonathan C Balloch, Varun Agrawal, Irfan Essa +1
Robot perception systems need to perform reliable image segmentation in real-time on noisy, raw perception data. State-of-the-art segmentation approaches use large CNN models and c…
Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition
Unaiza Ahsan, Rishi Madhok, Irfan Essa
We propose a self-supervised learning method to jointly reason about spatial and temporal context for video recognition. Recent self-supervised approaches have used spatial context…
End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features
Chiori Hori, Huda Alamri, Jue Wang +10
Dialog systems need to understand dynamic visual scenes in order to have conversations with users about the objects and events around them. Scene-aware dialog systems for real-worl…
Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7
Huda Alamri, Vincent Cartillier, Raphael Gontijo Lopes +8
Scene-aware dialog systems will be able to have conversations with users about the objects and events around them. Progress on such systems can be made by integrating state-of-the-…
Surgical Activity Recognition in Robot-Assisted Radical Prostatectomy using Deep Learning
Aneeq Zia, Andrew Hung, Irfan Essa +1
Adverse surgical outcomes are costly to patients and hospitals. Approaches to benchmark surgical care are often limited to gross measures across the entire procedure despite the pe…
Efficient Hierarchical Graph-Based Segmentation of RGBD Videos
Steven Hickson, Stan Birchfield, Irfan Essa +1
We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based…
Let's Dance: Learning From Online Dance Videos
Daniel Castro, Steven Hickson, Patsorn Sangkloy +4
In recent years, deep neural network approaches have naturally extended to the video domain, in their simplest case by aggregating per-frame classifications as a baseline for actio…
DiscrimNet: Semi-Supervised Action Recognition from Videos using Generative Adversarial Networks
Unaiza Ahsan, Chen Sun, Irfan Essa
We propose an action recognition framework using Gen- erative Adversarial Networks. Our model involves train- ing a deep convolutional generative adversarial network (DCGAN) using…
Object category learning and retrieval with weak supervision
Steven Hickson, Anelia Angelova, Irfan Essa +1
We consider the problem of retrieving objects from image data and learning to classify them into meaningful semantic categories with minimal supervision. To that end, we propose a…