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Found 5 papers, 2 papers with code
SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification
This paper introduces the first public large-scale, long-span dataset with sea turtle photographs captured in the wild -- SeaTurtleID2022 (https://www. kaggle. com/datasets/wildlifedatasets/seaturtleid2022).
VinVL+L: Enriching Visual Representation with Location Context in VQA
In this paper, we describe a novel method - VinVL+L - that enriches the visual representations (i. e. object tags and region features) of the State-of-the-Art Vision and Language (VL) method - VinVL - with Location information.
Ranked #10 on
Visual Question Answering (VQA)
on GQA Test2019
SeaTurtleID: A novel long-span dataset highlighting the importance of timestamps in wildlife re-identification
We show that time-unaware (random) splits can lead to performance overestimation of more than 100% compared to the time-aware splits for both feature- and CNN-based re-identification methods.
Danish Fungi 2020 -- Not Just Another Image Recognition Dataset
Interestingly, ViT achieves results superior to CNN baselines with 80. 45% accuracy and 0. 743 macro F1 score, reducing the CNN error by 9% and 12% respectively.
Ranked #1 on
Image Classification
on DF20
Mastering Large Scale Multi-label Image Recognition with high efficiency overCamera trap images
Camera traps are crucial in biodiversity motivated studies, however dealing with large number of images while annotating these data sets is a tedious and time consuming task.
