4 citations · 7 across the 7 of their papers we have counts for
7 papers
Dusk Till Dawn: Self-supervised Nighttime Stereo Depth Estimation using Visual Foundation Models
Madhu Vankadari, Samuel Hodgson, Sangyun Shin +2
Self-supervised depth estimation algorithms rely heavily on frame-warping relationships, exhibiting substantial performance degradation when applied in challenging circumstances, s…
Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation
Sangyun Shin, Kaichen Zhou, Madhu Vankadari +2
Coarse-to-fine 3D instance segmentation methods show weak performances compared to recent Grouping-based, Kernel-based and Transformer-based methods. We argue that this is due to t…
Tighter Variational Bounds are Not Necessarily Better. A Research Report on Implementation, Ablation Study, and Extensions
Amine M'Charrak, Vít Růžička, Sangyun Shin +1
This report explains, implements and extends the works presented in "Tighter Variational Bounds are Not Necessarily Better" (T Rainforth et al., 2018). We provide theoretical and e…
Sample, Crop, Track: Self-Supervised Mobile 3D Object Detection for Urban Driving LiDAR
Sangyun Shin, Stuart Golodetz, Madhu Vankadari +3
Deep learning has led to great progress in the detection of mobile (i.e. movement-capable) objects in urban driving scenes in recent years. Supervised approaches typically require…
When the Sun Goes Down: Repairing Photometric Losses for All-Day Depth Estimation
Madhu Vankadari, Stuart Golodetz, Sourav Garg +3
Self-supervised deep learning methods for joint depth and ego-motion estimation can yield accurate trajectories without needing ground-truth training data. However, as they typical…
Real-Time Hybrid Mapping of Populated Indoor Scenes using a Low-Cost Monocular UAV
Stuart Golodetz, Madhu Vankadari, Aluna Everitt +3
Unmanned aerial vehicles (UAVs) have been used for many applications in recent years, from urban search and rescue, to agricultural surveying, to autonomous underground mine explor…
Unsupervised Monocular Depth Estimation for Night-time Images using Adversarial Domain Feature Adaptation
Madhu Vankadari, Sourav Garg, Anima Majumder +2
In this paper, we look into the problem of estimating per-pixel depth maps from unconstrained RGB monocular night-time images which is a difficult task that has not been addressed…