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Hemal Naik

3 accepted papers

2026

CHIRP dataset: towards long-term, individual-level, behavioral monitoring of bird populations in the wild

Alex Hoi Hang Chan, Neha Singhal, Onur Kocahan, Andrea Meltzer, Saverio Lubrano, Miyako H. Warrington +3
CVPR 2026

Long-term behavioral monitoring of individual animals is crucial for studying behavioral changes that occurs over different time scales, especially for conservation and evolutionary biology. Computer vision methods have proven to benefit biodiversity monitoring, but automated behavior monitoring in

Cited by 0Source ↗code ↗Scholar ↗
2024

BuckTales: A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes

Hemal Naik, Junran Yang, Dipin Das, Margaret C Crofoot, Akanksha Rathore, Vivek H Sridhar
NeurIPS 2024poster

Understanding animal behaviour is central to predicting, understanding, and miti- gating impacts of natural and anthropogenic changes on animal populations and ecosystems. However, the challenges of acquiring and processing long-term, eco- logically relevant data in wild settings have constrained th…

Cited by 1Source ↗PDF ↗Scholar ↗
2023

3D-POP - An Automated Annotation Approach to Facilitate Markerless 2D-3D Tracking of Freely Moving Birds With Marker-Based Motion Capture

Hemal Naik, Alex Hoi Hang Chan, Junran Yang, Mathilde Delacoux, Iain D. Couzin, Fumihiro Kano +1
CVPR 2023poster

Recent advances in machine learning and computer vision are revolutionizing the field of animal behavior by enabling researchers to track the poses and locations of freely moving animals without any marker attachment. However, large datasets of annotated images of animals for markerless pose trackin…

Cited by 28Source ↗PDF ↗code ↗Scholar ↗