activity
20162022
most citedHybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

477 citations · 638 across the 31 of their papers we have counts for

collaborators

50 papers

cs.CV20229 cited

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…

cs.CV20229 cited

AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments

Sudipta Paul, Amit K. Roy-Chowdhury, Anoop Cherian

Recent years have seen embodied visual navigation advance in two distinct directions: (i) in equipping the AI agent to follow natural language instructions, and (ii) in making the…

cs.CV20223 cited

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,…

cs.CV2022

Cross-Modal Knowledge Transfer Without Task-Relevant Source Data

Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng +2

Cost-effective depth and infrared sensors as alternatives to usual RGB sensors are now a reality, and have some advantages over RGB in domains like autonomous navigation and remote…

cs.CV2022

A-ACT: Action Anticipation through Cycle Transformations

Akash Gupta, Jingen Liu, Liefeng Bo +2

While action anticipation has garnered a lot of research interest recently, most of the works focus on anticipating future action directly through observed visual cues only. In thi…

cs.CV20222 cited

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…