132 citations · 301 across the 18 of their papers we have counts for
22 papers · 1 filter
ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements
Bryan Bo Cao, Abrar Alali, Hansi Liu +5
Tracking subjects in videos is one of the most widely used functions in camera-based IoT applications such as security surveillance, smart city traffic safety enhancement, vehicle…
Learning a Pedestrian Social Behavior Dictionary
Faith Johnson, Kristin Dana
Understanding pedestrian behavior patterns is a key component to building autonomous agents that can navigate among humans. We seek a learned dictionary of pedestrian behavior to o…
ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning
Nicholas Meegan, Hansi Liu, Bryan Bo Cao +5
We introduce ViFiCon, a self-supervised contrastive scheme which learns a cross-modal association between vision and wireless modalities. Specifically, the system uses pedestrian d…
Towards Single Stage Weakly Supervised Semantic Segmentation
Peri Akiva, Kristin Dana
The costly process of obtaining semantic segmentation labels has driven research towards weakly supervised semantic segmentation (WSSS) methods, using only image-level, point, or b…
AI on the Bog: Monitoring and Evaluating Cranberry Crop Risk
Peri Akiva, Benjamin Planche, Aditi Roy +3
Machine vision for precision agriculture has attracted considerable research interest in recent years. The goal of this paper is to develop an end-to-end cranberry health monitorin…
H2O-Net: Self-Supervised Flood Segmentation via Adversarial Domain Adaptation and Label Refinement
Peri Akiva, Matthew Purri, Kristin Dana +2
Accurate flood detection in near real time via high resolution, high latency satellite imagery is essential to prevent loss of lives by providing quick and actionable information.…
Differential Viewpoints for Ground Terrain Material Recognition
Jia Xue, Hang Zhang, Ko Nishino +1
Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based repres…
Angular Luminance for Material Segmentation
Jia Xue, Matthew Purri, Kristin Dana
Moving cameras provide multiple intensity measurements per pixel, yet often semantic segmentation, material recognition, and object recognition do not utilize this information. Wit…
Feudal Steering: Hierarchical Learning for Steering Angle Prediction
Faith Johnson, Kristin Dana
We consider the challenge of automated steering angle prediction for self driving cars using egocentric road images. In this work, we explore the use of feudal networks, used in hi…
Finding Berries: Segmentation and Counting of Cranberries using Point Supervision and Shape Priors
Peri Akiva, Kristin Dana, Peter Oudemans +1
Precision agriculture has become a key factor for increasing crop yields by providing essential information to decision makers. In this work, we present a deep learning method for…
Teaching Cameras to Feel: Estimating Tactile Physical Properties of Surfaces From Images
Matthew Purri, Kristin Dana
The connection between visual input and tactile sensing is critical for object manipulation tasks such as grasping and pushing. In this work, we introduce the challenging task of e…
Material Segmentation of Multi-View Satellite Imagery
Matthew Purri, Jia Xue, Kristin Dana +5
Material recognition methods use image context and local cues for pixel-wise classification. In many cases only a single image is available to make a material prediction. Image seq…
Deep Texture Manifold for Ground Terrain Recognition
Jia Xue, Hang Zhang, Kristin Dana
We present a texture network called Deep Encoding Pooling Network (DEP) for the task of ground terrain recognition. Recognition of ground terrain is an important task in establishi…
Context Encoding for Semantic Segmentation
Hang Zhang, Kristin Dana, Jianping Shi +4
Recent work has made significant progress in improving spatial resolution for pixelwise labeling with Fully Convolutional Network (FCN) framework by employing Dilated/Atrous convol…
Photo-realistic Facial Texture Transfer
Parneet Kaur, Hang Zhang, Kristin J. Dana
Style transfer methods have achieved significant success in recent years with the use of convolutional neural networks. However, many of these methods concentrate on artistic style…
Multi-style Generative Network for Real-time Transfer
Hang Zhang, Kristin Dana
Despite the rapid progress in style transfer, existing approaches using feed-forward generative network for multi-style or arbitrary-style transfer are usually compromised of image…
Deep TEN: Texture Encoding Network
Hang Zhang, Jia Xue, Kristin Dana
We propose a Deep Texture Encoding Network (Deep-TEN) with a novel Encoding Layer integrated on top of convolutional layers, which ports the entire dictionary learning and encoding…
Differential Angular Imaging for Material Recognition
Jia Xue, Hang Zhang, Kristin Dana +1
Material recognition for real-world outdoor surfaces has become increasingly important for computer vision to support its operation "in the wild." Computational surface modeling th…
Reading Between the Pixels: Photographic Steganography for Camera Display Messaging
Eric Wengrowski, Kristin Dana, Marco Gruteser +1
We exploit human color metamers to send light-modulated messages less visible to the human eye, but recoverable by cameras. These messages are a key component to camera-display mes…
Friction from Reflectance: Deep Reflectance Codes for Predicting Physical Surface Properties from One-Shot In-Field Reflectance
Hang Zhang, Kristin Dana, Ko Nishino
Images are the standard input for vision algorithms, but one-shot infield reflectance measurements are creating new opportunities for recognition and scene understanding. In this w…
Reflectance Hashing for Material Recognition
Hang Zhang, Kristin Dana, Ko Nishino
We introduce a novel method for using reflectance to identify materials. Reflectance offers a unique signature of the material but is challenging to measure and use for recognizing…
Optimal Radiometric Calibration for Camera-Display Communication
Wenjia Yuan, Eric Wengrowski, Kristin J. Dana +3
We present a novel method for communicating between a camera and display by embedding and recovering hidden and dynamic information within a displayed image. A handheld camera poin…