Sara Beery

Orcid: 0000-0002-2544-1844

Affiliations:
  • Massachusetts Institute of Technology, USA
  • California Institute of Technology, USA (former)


According to our database1, Sara Beery authored at least 36 papers between 2016 and 2024.

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Timeline

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Bibliography

2024
Learning Hierarchical Semantic Classification by Grounding on Consistent Image Segmentations.
CoRR, 2024

Application-Driven Innovation in Machine Learning.
CoRR, 2024

Align and Distill: Unifying and Improving Domain Adaptive Object Detection.
CoRR, 2024

Are They the Same Picture? Adapting Concept Bottleneck Models for Human-AI Collaboration in Image Retrieval.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Position: Application-Driven Innovation in Machine Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors.
Proceedings of the Computer Vision - ECCV 2024, 2024

Monitoring Social Insect Activity with Minimal Human Supervision.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Reflections from the Workshop on AI-Assisted Decision Making for Conservation.
CoRR, 2023

Vision Models Can Be Efficiently Specialized via Few-Shot Task-Aware Compression.
CoRR, 2023

Teaching Computer Vision for Ecology.
CoRR, 2023

MammalNet: A Large-Scale Video Benchmark for Mammal Recognition and Behavior Understanding.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Extending the WILDS Benchmark for Unsupervised Adaptation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting.
Proceedings of the Computer Vision - ECCV 2022, 2022

The Auto Arborist Dataset: A Large-Scale Benchmark for Multiview Urban Forest Monitoring Under Domain Shift.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Scaling biodiversity monitoring for the data age.
XRDS, 2021

Seeing biodiversity: perspectives in machine learning for wildlife conservation.
CoRR, 2021

Domain Adaptation for Rare Classes Augmented with Synthetic Samples.
CoRR, 2021

Image-to-Image Translation of Synthetic Samples for Rare Classes.
CoRR, 2021

Can poachers find animals from public camera trap images?
CoRR, 2021

The iWildCam 2021 Competition Dataset.
CoRR, 2021


ElephantBook: A Semi-Automated Human-in-the-Loop System for Elephant Re-Identification.
Proceedings of the COMPASS '21: ACM SIGCAS Conference on Computing and Sustainable Societies, Virtual Event, Australia, 28 June 2021, 2021

Species Distribution Modeling for Machine Learning Practitioners: A Review.
Proceedings of the COMPASS '21: ACM SIGCAS Conference on Computing and Sustainable Societies, Virtual Event, Australia, 28 June 2021, 2021

Benchmarking Representation Learning for Natural World Image Collections.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts.
CoRR, 2020

The iWildCam 2020 Competition Dataset.
CoRR, 2020

Synthetic Examples Improve Generalization for Rare Classes.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Long Term Temporal Context for Per-Camera Object Detection.
CoRR, 2019

A deep active learning system for species identification and counting in camera trap images.
CoRR, 2019

The iWildCam 2019 Challenge Dataset.
CoRR, 2019

Efficient Pipeline for Camera Trap Image Review.
CoRR, 2019

The iWildCam 2018 Challenge Dataset.
CoRR, 2019

Synthetic Examples Improve Generalization for Rare Classes.
CoRR, 2019

2018
Recognition in Terra Incognita.
Proceedings of the Computer Vision - ECCV 2018, 2018

2016
Finding areas of motion in camera trap images.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016


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