7 papers
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…
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…
Assessment of the synthetic feasibility of hypothetical zeolite-like materials based on ZeoNet
Yachan Liu, Elaine Wu, Ping Yang +4
A suite of classifiers was developed to distinguish experimentally synthesized zeolites from computationally predicted zeolite-like structures. Using convolutional neural networks…
Not All Birds Look The Same: Identity-Preserving Generation For Birds
Aaron Sun, Oindrila Saha, Subhransu Maji
Since the advent of controllable image generation, increasingly rich modes of control have enabled greater customization and accessibility for everyday users. Zero-shot, identity-p…
Merlin L48 Spectrogram Dataset
Aaron Sun, Subhransu Maji, Grant Van Horn
In the single-positive multi-label (SPML) setting, each image in a dataset is labeled with the presence of a single class, while the true presence of other classes remains unknown.…
Task2Box: Box Embeddings for Modeling Asymmetric Task Relationships
Rangel Daroya, Aaron Sun, Subhransu Maji
Modeling and visualizing relationships between tasks or datasets is an important step towards solving various meta-tasks such as dataset discovery, multi-tasking, and transfer lear…
COSE: A Consistency-Sensitivity Metric for Saliency on Image Classification
Rangel Daroya, Aaron Sun, Subhransu Maji
We present a set of metrics that utilize vision priors to effectively assess the performance of saliency methods on image classification tasks. To understand behavior in deep learn…