2 citations · 4 across the 5 of their papers we have counts for
5 papers
FAVE: Foveated Adaptive Visual Encoding for Efficient Fine-Grained Visual Understanding
Amitangshu Mukherjee, Kaushik Roy
Fine-grained visual understanding depends on local detail, yet visual encoders face a trade-off between costly full-image high-resolution processing and compact global encoding tha…
Towards Two-Stream Foveation-based Active Vision Learning
Timur Ibrayev, Amitangshu Mukherjee, Sai Aparna Aketi +1
Deep neural network (DNN) based machine perception frameworks process the entire input in a one-shot manner to provide answers to both "what object is being observed" and "where it…
On Inherent Adversarial Robustness of Active Vision Systems
Amitangshu Mukherjee, Timur Ibrayev, Kaushik Roy
Current Deep Neural Networks are vulnerable to adversarial examples, which alter their predictions by adding carefully crafted noise. Since human eyes are robust to such inputs, it…
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift
Amitangshu Mukherjee, Isha Garg, Kaushik Roy
Over the past decade, deep neural networks have proven to be adept in image classification tasks, often surpassing humans in terms of accuracy. However, standard neural networks of…
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
Ameya Joshi, Amitangshu Mukherjee, Soumik Sarkar +1
Deep neural networks have been shown to exhibit an intriguing vulnerability to adversarial input images corrupted with imperceptible perturbations. However, the majority of adversa…