62 citations · 76 across the 10 of their papers we have counts for
10 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…
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…
Image Masking for Robust Self-Supervised Monocular Depth Estimation
Hemang Chawla, Kishaan Jeeveswaran, Elahe Arani +1
Self-supervised monocular depth estimation is a salient task for 3D scene understanding. Learned jointly with monocular ego-motion estimation, several methods have been proposed to…
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…
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…
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos
Hemang Chawla, Matti Jukola, Shabbir Marzban +2
Spatial scene-understanding, including dense depth and ego-motion estimation, is an important problem in computer vision for autonomous vehicles and advanced driver assistance syst…
Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning Approach
Hemang Chawla, Matti Jukola, Terence Brouns +2
The ability to efficiently utilize crowdsourced visual data carries immense potential for the domains of large scale dynamic mapping and autonomous driving. However, state-of-the-a…
Monocular Vision based Crowdsourced 3D Traffic Sign Positioning with Unknown Camera Intrinsics and Distortion Coefficients
Hemang Chawla, Matti Jukola, Elahe Arani +1
Autonomous vehicles and driver assistance systems utilize maps of 3D semantic landmarks for improved decision making. However, scaling the mapping process as well as regularly upda…