113 citations · 463 across the 36 of their papers we have counts for
23 papers · 1 filter
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…
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…
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…
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…
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…
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.…
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…
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition
Jiaming Liu, M. Salman Asif, Brendt Wohlberg +1
The plug-and-play priors (PnP) and regularization by denoising (RED) methods have become widely used for solving inverse problems by leveraging pre-trained deep denoisers as image…
Alternating Phase Projected Gradient Descent with Generative Priors for Solving Compressive Phase Retrieval
Rakib Hyder, Viraj Shah, Chinmay Hegde +1
The classical problem of phase retrieval arises in various signal acquisition systems. Due to the ill-posed nature of the problem, the solution requires assumptions on the structur…
Generative Models for Low-Rank Video Representation and Reconstruction
Rakib Hyder, M. Salman Asif
Finding compact representation of videos is an essential component in almost every problem related to video processing or understanding. In this paper, we propose a generative mode…
Toward Depth Estimation Using Mask-Based Lensless Cameras
M. Salman Asif
Recently, coded masks have been used to demonstrate a thin form-factor lensless camera, FlatCam, in which a mask is placed immediately on top of a bare image sensor. In this paper,…
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…
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…
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…