From the 1 of 7 linked papers with an AI index.
7 papers
MetaPerch: Learning from metadata for bioacoustics foundation models
Mustafa Chasmai, Vincent Dumoulin, Jenny Hamer
The paper presents MetaPerch, a bioacoustic foundation model that uses recording metadata (e.g., location, time) as auxiliary supervision to improve species identification performa…
WildProp: Visual Estimation of Wildlife Body Proportions at Scale
Mustafa Chasmai, Aaron Sun, Subhransu Maji
Population-level morphometric measurements underpin ecological and evolutionary studies but traditionally require controlled imaging or physical specimen handling, limiting scalabi…
Bioacoustic Geolocation: Species Sounds as Geographic Signals
Mustafa Chasmai, Wuao Liu, Subhransu Maji +1
Can we determine someone's geographic location solely from the sounds they hear? Are acoustic signals enough to localize within a country, state, or even city? In this work, we tac…
Masked Autoencoders with Limited Data: Does It Work? A Fine-Grained Bioacoustics Case Study
Wuao Liu, Mustafa Chasmai, Subhransu Maji +1
Bioacoustic recognition requires fine-grained acoustic understanding to distinguish similar-sounding species. However, many large-scale data repositories such as iNaturalist are we…
RealBirdID: Benchmarking Bird Species Identification in the Era of MLLMs
Logan Lawrence, Mustafa Chasmai, Rangel Daroya +8
Fine-grained bird species identification in the wild is frequently unanswerable from a single image: key cues may be non-visual (e.g. vocalization), or obscured due to occlusion, c…
Moment Sampling in Video LLMs for Long-Form Video QA
Mustafa Chasmai, Gauri Jagatap, Gouthaman KV +3
Recent advancements in video large language models (Video LLMs) have significantly advanced the field of video question answering (VideoQA). While existing methods perform well on…