IIM-TTIJ/MVA2025-SMOT4SB

Official repository for the MVA2025 SMOT4SB Challenge. Provides dataset, baseline code, and evaluation scripts for the Small Multi-Object Tracking for Spotting Birds (SMOT4SB) competition, focusing on UAV-based small bird tracking.

37
/ 100
Emerging

This project helps environmental researchers and conservationists automatically track small birds in drone footage. You provide video data captured by a UAV, and it outputs precise locations and identities of individual birds over time, even for very small or numerous targets. This is designed for specialists working on wildlife monitoring and ecological studies.

No commits in the last 6 months.

Use this if you need to accurately count and track individual small birds in drone-recorded video sequences to monitor populations or behavior.

Not ideal if your primary goal is simple bird detection without needing to track their movement, or if you are working with large, easily identifiable animal species.

wildlife-monitoring ornithology UAV-ecology animal-tracking conservation-biology
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

14

Forks

3

Language

Python

License

MIT

Last pushed

Jul 17, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/IIM-TTIJ/MVA2025-SMOT4SB"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.