131 citations · 648 across the 42 of their papers we have counts for
24 papers · 1 filter
LFD: Enabling Real-World Lensless Face Recognition with a Large-Scale Dataset
Junho Kim, Salman S. Khan, Sara Wan +2
Face recognition is a ubiquitously used computer vision task that has a wide range of applications ranging from everyday smartphone biometrics to high-stakes security systems. Most…
NeRT: Implicit Neural Representations for General Unsupervised Turbulence Mitigation
Weiyun Jiang, Yuhao Liu, Vivek Boominathan +1
The atmospheric and water turbulence mitigation problems have emerged as challenging inverse problems in computer vision and optics communities over the years. However, current met…
Thermal Spread Functions (TSF): Physics-guided Material Classification
Aniket Dashpute, Vishwanath Saragadam, Emma Alexander +4
Robust and non-destructive material classification is a challenging but crucial first-step in numerous vision applications. We propose a physics-guided material classification fram…
WIRE: Wavelet Implicit Neural Representations
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan +3
Implicit neural representations (INRs) have recently advanced numerous vision-related areas. INR performance depends strongly on the choice of the nonlinear activation function emp…
ORCa: Glossy Objects as Radiance Field Cameras
Kushagra Tiwary, Akshat Dave, Nikhil Behari +3
Reflections on glossy objects contain valuable and hidden information about the surrounding environment. By converting these objects into cameras, we can unlock exciting applicatio…
PANDORA: Polarization-Aided Neural Decomposition Of Radiance
Akshat Dave, Yongyi Zhao, Ashok Veeraraghavan
Reconstructing an object's geometry and appearance from multiple images, also known as inverse rendering, is a fundamental problem in computer graphics and vision. Inverse renderin…
MINER: Multiscale Implicit Neural Representations
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan +2
We introduce a new neural signal model designed for efficient high-resolution representation of large-scale signals. The key innovation in our multiscale implicit neural representa…
CodedStereo: Learned Phase Masks for Large Depth-of-field Stereo
Shiyu Tan, Yicheng Wu, Shoou-I Yu +1
Conventional stereo suffers from a fundamental trade-off between imaging volume and signal-to-noise ratio (SNR) -- due to the conflicting impact of aperture size on both these vari…
Fine-grained Classification using Heterogeneous Web Data and Auxiliary Categories
Li Niu, Ashok Veeraraghavan, Ashu Sabharwal
Fine-grained classification remains a very challenging problem, because of the absence of well-labeled training data caused by the high cost of annotating a large number of fine-gr…
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning
Wanjia Liu, Huaijin Chen, Rishab Goel +3
Good temporal representations are crucial for video understanding, and the state-of-the-art video recognition framework is based on two-stream networks. In such framework, besides…
Learning from Noisy Web Data with Category-level Supervision
Li Niu, Qingtao Tang, Ashok Veeraraghavan +1
As tons of photos are being uploaded to public websites (e.g., Flickr, Bing, and Google) every day, learning from web data has become an increasingly popular research direction bec…
Reblur2Deblur: Deblurring Videos via Self-Supervised Learning
Huaijin Chen, Jinwei Gu, Orazio Gallo +3
Motion blur is a fundamental problem in computer vision as it impacts image quality and hinders inference. Traditional deblurring algorithms leverage the physics of the image forma…
Zero-Shot Learning via Category-Specific Visual-Semantic Mapping
Li Niu, Jianfei Cai, Ashok Veeraraghavan
Zero-Shot Learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories, in which the gap between seen categories and…
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels
Huaijin Chen, Suren Jayasuriya, Jiyue Yang +4
Deep learning using convolutional neural networks (CNNs) is quickly becoming the state-of-the-art for challenging computer vision applications. However, deep learning's power consu…
Spatial Phase-Sweep: Increasing temporal resolution of transient imaging using a light source array
Ryuichi Tadano, Adithya Kumar Pediredla, Kaushik Mitra +1
Transient imaging or light-in-flight techniques capture the propagation of an ultra-short pulse of light through a scene, which in effect captures the optical impulse response of t…
Toward Long Distance, Sub-diffraction Imaging Using Coherent Camera Arrays
Jason Holloway, M. Salman Asif, Manoj Kumar Sharma +4
In this work, we propose using camera arrays coupled with coherent illumination as an effective method of improving spatial resolution in long distance images by a factor of ten an…
Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging
Suren Jayasuriya, Adithya Pediredla, Sriram Sivaramakrishnan +2
A variety of techniques such as light field, structured illumination, and time-of-flight (TOF) are commonly used for depth acquisition in consumer imaging, robotics and many other…
FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation
M. Salman Asif, Ali Ayremlou, Aswin Sankaranarayanan +2
FlatCam is a thin form-factor lensless camera that consists of a coded mask placed on top of a bare, conventional sensor array. Unlike a traditional, lens-based camera where an ima…
TabletGaze: Unconstrained Appearance-based Gaze Estimation in Mobile Tablets
Qiong Huang, Ashok Veeraraghavan, Ashutosh Sabharwal
We study gaze estimation on tablets, our key design goal is uncalibrated gaze estimation using the front-facing camera during natural use of tablets, where the posture and method o…
FPA-CS: Focal Plane Array-based Compressive Imaging in Short-wave Infrared
Huaijin Chen, M. Salman Asif, Aswin C. Sankaranarayanan +1
Cameras for imaging in short and mid-wave infrared spectra are significantly more expensive than their counterparts in visible imaging. As a result, high-resolution imaging in thos…
DistancePPG: Robust non-contact vital signs monitoring using a camera
Mayank Kumar, Ashok Veeraraghavan, Ashutosh Sabharval
Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital set…
Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit
Ali Ayremlou, Thomas Goldstein, Ashok Veeraraghavan +1
Sparse approximations using highly over-complete dictionaries is a state-of-the-art tool for many imaging applications including denoising, super-resolution, compressive sensing, l…
A Framework for the Analysis of Computational Imaging Systems with Practical Applications
Kaushik Mitra, Oliver Cossairt, Ashok Veeraraghavan
Over the last decade, a number of Computational Imaging (CI) systems have been proposed for tasks such as motion deblurring, defocus deblurring and multispectral imaging. These tec…
Progressive versus Random Projections for Compressive Capture of Images, Lightfields and Higher Dimensional Visual Signals
Rohit Pandharkar, Ashok Veeraraghavan, Ramesh Raskar
Computational photography involves sophisticated capture methods. A new trend is to capture projection of higher dimensional visual signals such as videos, multi-spectral data and…