62 citations · 73 across the 9 of their papers we have counts for
9 papers
Transformers in Unsupervised Structure-from-Motion
Hemang Chawla, Arnav Varma, Elahe Arani +1
Transformers have revolutionized deep learning based computer vision with improved performance as well as robustness to natural corruptions and adversarial attacks. Transformers ar…
Continual Learning of Unsupervised Monocular Depth from Videos
Hemang Chawla, Arnav Varma, Elahe Arani +1
Spatial scene understanding, including monocular depth estimation, is an important problem in various applications, such as robotics and autonomous driving. While improvements in u…
Dynamically Modular and Sparse General Continual Learning
Arnav Varma, Elahe Arani, Bahram Zonooz
Real-world applications often require learning continuously from a stream of data under ever-changing conditions. When trying to learn from such non-stationary data, deep neural ne…
AI-Driven Road Maintenance Inspection v2: Reducing Data Dependency & Quantifying Road Damage
Haris Iqbal, Hemang Chawla, Arnav Varma +4
Road infrastructure maintenance inspection is typically a labor-intensive and critical task to ensure the safety of all road users. Existing state-of-the-art techniques in Artifici…
Adversarial Attacks on Monocular Pose Estimation
Hemang Chawla, Arnav Varma, Elahe Arani +1
Advances in deep learning have resulted in steady progress in computer vision with improved accuracy on tasks such as object detection and semantic segmentation. Nevertheless, deep…
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsics
Arnav Varma, Hemang Chawla, Bahram Zonooz +1
The advent of autonomous driving and advanced driver assistance systems necessitates continuous developments in computer vision for 3D scene understanding. Self-supervised monocula…
A Comprehensive Study of Vision Transformers on Dense Prediction Tasks
Kishaan Jeeveswaran, Senthilkumar Kathiresan, Arnav Varma +3
Convolutional Neural Networks (CNNs), architectures consisting of convolutional layers, have been the standard choice in vision tasks. Recent studies have shown that Vision Transfo…
Highlighting the Importance of Reducing Research Bias and Carbon Emissions in CNNs
Ahmed Badar, Arnav Varma, Adrian Staniec +5
Convolutional neural networks (CNNs) have become commonplace in addressing major challenges in computer vision. Researchers are not only coming up with new CNN architectures but ar…
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation
Hemang Chawla, Arnav Varma, Elahe Arani +1
Dense depth estimation is essential to scene-understanding for autonomous driving. However, recent self-supervised approaches on monocular videos suffer from scale-inconsistency ac…