1 citations · 1 across the 5 of their papers we have counts for
5 papers
WildBox: A Dataset and Benchmark for Aerial Monocular 3D Detection of African Savanna Wildlife
Vandita Shukla, Kilian Meier, Lucie Laporte-Devylder +6
We introduce WildBox, a dataset and benchmark for monocular 3D detection of wildlife from drone video, comprising 237,505 3D bounding box annotations across seven African savanna s…
FAIR^2 Drones: An AI-Ready Standard for Cross-Domain Wildlife Drone Datasets
Jenna Kline, Kilian Meier, Vandita Shukla +14
Animal ecology data collection using drones represents a substantial investment of time, expertise, and financial resources. Yet most existing datasets serve only a single research…
WildLIFT: Lifting monocular drone video to 3D for species-agnostic wildlife monitoring
Vandita Shukla, Fabio Remondino, Blair Costelloe +1
Monocular RGB cameras mounted on drones are widely used for wildlife monitoring, yet most analytical pipelines remain confined to two-dimensional image space, leaving geometric inf…
Adding Another Dimension to Image-based Animal Detection
Vandita Shukla, Fabio Remondino, Benjamin Risse
Monocular imaging of animals inherently reduces 3D structures to 2D projections. Detection algorithms lead to 2D bounding boxes that lack information about animal's orientation rel…
Exploring the potential of collaborative UAV 3D mapping in Kenyan savanna for wildlife research
Vandita Shukla, Luca Morelli, Pawel Trybala +4
UAV-based biodiversity conservation applications have exhibited many data acquisition advantages for researchers. UAV platforms with embedded data processing hardware can support c…