113 citations · 463 across the 36 of their papers we have counts for
42 papers
Provable and Robust Wavefront Sensing via Self-Reference Interferometry
Nebiyou Yismaw, Vishwanath Saragadam, Aswin C. Sankaranarayanan +1
Wavefront sensing involves estimating the phase and intensity of light, enabling a wide range of imaging applications, from adaptive optics and astronomy to biomedical imaging. Sin…
MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
Md Kaykobad Reza, Ashley Prater-Bennette, M. Salman Asif
Leveraging information across diverse modalities is known to enhance performance on multimodal segmentation tasks. However, effectively fusing information from different modalities…
On The Application Of Log Compression and Enhanced Denoising In Contrast Enhancement Of Digital Radiography Images
M. S. Asif, Mahesh Raveendranatha Panicker
Digital radiography (DR) is becoming popular for the point of care imaging in the recent past. To reduce the radiation exposure, controlled radiation based on as low as reasonably…
DNeRV: Modeling Inherent Dynamics via Difference Neural Representation for Videos
Qi Zhao, M. Salman Asif, Zhan Ma
Existing implicit neural representation (INR) methods do not fully exploit spatiotemporal redundancies in videos. Index-based INRs ignore the content-specific spatial features and…
Ensemble-based Blackbox Attacks on Dense Prediction
Zikui Cai, Yaoteng Tan, M. Salman Asif
We propose an approach for adversarial attacks on dense prediction models (such as object detectors and segmentation). It is well known that the attacks generated by a single surro…
Compressive Sensing with Tensorized Autoencoder
Rakib Hyder, M. Salman Asif
Deep networks can be trained to map images into a low-dimensional latent space. In many cases, different images in a collection are articulated versions of one another; for example…
Disguise without Disruption: Utility-Preserving Face De-Identification
Zikui Cai, Zhongpai Gao, Benjamin Planche +4
With the rise of cameras and smart sensors, humanity generates an exponential amount of data. This valuable information, including underrepresented cases like AI in medical setting…
Coded Illumination for 3D Lensless Imaging
Yucheng Zheng, M. Salman Asif
Mask-based lensless cameras offer a novel design for imaging systems by replacing the lens in a conventional camera with a layer of coded mask. Each pixel of the lensless camera en…
Efficient Visual Computing with Camera RAW Snapshots
Zhihao Li, Ming Lu, Xu Zhang +3
Conventional cameras capture image irradiance on a sensor and convert it to RGB images using an image signal processor (ISP). The images can then be used for photography or visual…
GAMA: Generative Adversarial Multi-Object Scene Attacks
Abhishek Aich, Calvin-Khang Ta, Akash Gupta +4
The majority of methods for crafting adversarial attacks have focused on scenes with a single dominant object (e.g., images from ImageNet). On the other hand, natural scenes includ…
Leveraging Local Patch Differences in Multi-Object Scenes for Generative Adversarial Attacks
Abhishek Aich, Shasha Li, Chengyu Song +3
State-of-the-art generative model-based attacks against image classifiers overwhelmingly focus on single-object (i.e., single dominant object) images. Different from such settings,…
H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System
Ming Cheng, Yiling Xu, Wang Shen +4
High-speed, high-resolution stereoscopic (H2-Stereo) video allows us to perceive dynamic 3D content at fine granularity. The acquisition of H2-Stereo video, however, remains challe…
Blackbox Attacks via Surrogate Ensemble Search
Zikui Cai, Chengyu Song, Srikanth Krishnamurthy +2
Blackbox adversarial attacks can be categorized into transfer- and query-based attacks. Transfer methods do not require any feedback from the victim model, but provide lower succes…
Incremental Task Learning with Incremental Rank Updates
Rakib Hyder, Ken Shao, Boyu Hou +3
Incremental Task learning (ITL) is a category of continual learning that seeks to train a single network for multiple tasks (one after another), where training data for each task i…
2022 Review of Data-Driven Plasma Science
Rushil Anirudh, Rick Archibald, M. Salman Asif +60
Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data…
Zero-Query Transfer Attacks on Context-Aware Object Detectors
Zikui Cai, Shantanu Rane, Alejandro E. Brito +4
Adversarial attacks perturb images such that a deep neural network produces incorrect classification results. A promising approach to defend against adversarial attacks on natural…
Provable and Efficient Continual Representation Learning
Yingcong Li, Mingchen Li, M. Salman Asif +1
In continual learning (CL), the goal is to design models that can learn a sequence of tasks without catastrophic forgetting. While there is a rich set of techniques for CL, relativ…
GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional Network
Armin Masoumian, Hatem A. Rashwan, Saddam Abdulwahab +2
Depth estimation is a challenging task of 3D reconstruction to enhance the accuracy sensing of environment awareness. This work brings a new solution with a set of improvements, wh…
Context-Aware Transfer Attacks for Object Detection
Zikui Cai, Xinxin Xie, Shasha Li +5
Blackbox transfer attacks for image classifiers have been extensively studied in recent years. In contrast, little progress has been made on transfer attacks for object detectors.…
Coded Illumination for Improved Lensless Imaging
Yucheng Zheng, M. Salman Asif
Mask-based lensless cameras can be flat, thin, and light-weight, which makes them suitable for novel designs of computational imaging systems with large surface areas and arbitrary…
Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations
Shasha Li, Abhishek Aich, Shitong Zhu +4
When compared to the image classification models, black-box adversarial attacks against video classification models have been largely understudied. This could be possible because,…
ADC: Adversarial attacks against object Detection that evade Context consistency checks
Mingjun Yin, Shasha Li, Chengyu Song +3
Deep Neural Networks (DNNs) have been shown to be vulnerable to adversarial examples, which are slightly perturbed input images which lead DNNs to make wrong predictions. To protec…
Exploiting Multi-Object Relationships for Detecting Adversarial Attacks in Complex Scenes
Mingjun Yin, Shasha Li, Zikui Cai +4
Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples. Recent research has shown that checking the intrinsic consistencies in th…
A Simple Framework for 3D Lensless Imaging with Programmable Masks
Yucheng Zheng, Yi Hua, Aswin C. Sankaranarayanan +1
Lensless cameras provide a framework to build thin imaging systems by replacing the lens in a conventional camera with an amplitude or phase mask near the sensor. Existing methods…