WildFin: An In-the-Wild Dataset for Fish Behavioral Recognition
Recent advances in field technology have led to a massive influx of in-the-wild video data for ecological science. The primary bottleneck in leveraging this data is the high cost of expert annotation. While computer vision offers a potential solution, current models frequently fail when deployed in complex marine environments. To characterize these failures, we introduce WildFin, a novel benchmark for fish behavior recognition collected and annotated by ecologists.WildFin spans two critical real-world paradigms: stationary cameras monitoring groups of fish and dynamic divers following individu
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- FuzzyOverlapping authors or contributors · 62%google-research/google-research →
“Shared author/contributor keys: sun”
- FuzzyOverlapping authors or contributors · 62%modular/modular →
“Shared author/contributor keys: liu”
- FuzzyOverlapping authors or contributors · 62%Zeyi-Lin/HivisionIDPhotos →
“Shared author/contributor keys: lin”
- FuzzyOverlapping authors or contributors · 62%hiyouga/LlamaFactory →
“Shared author/contributor keys: lin”
- LinkedLinked via arxiv author · 85%Abigail G. Grassick →
“WildFin: An In-the-Wild Dataset for Fish Behavioral Recognition”
- LinkedLinked via arxiv author · 85%Jerome Tze-Hou Hsu →
“WildFin: An In-the-Wild Dataset for Fish Behavioral Recognition”
- LinkedLinked via arxiv author · 85%Ethan Lin →
“WildFin: An In-the-Wild Dataset for Fish Behavioral Recognition”
- LinkedLinked via arxiv author · 85%Ziang Liu →
“WildFin: An In-the-Wild Dataset for Fish Behavioral Recognition”