Research output per year
Research output per year
Description
This public and freely available dataset contains a PyTorch code section for the SCM and TCM deep learning network components, an annotation dataset for video object detection in the PanAfrican2019 video dataset, and the detailed split of the videos into training/validation/test portions. The dataset is used in the ICCVW2019 paper "Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending". Note that this dataset does not contain the video data itself, which is held by the PanAfrican Programme. Full details of the contents are provided in the readme.txt file.
| Date made available | 28 Jan 2020 |
|---|---|
| Publisher | University of Bristol |
Keywords
- Deep Learning
- Video Annotation
- Computer Vision
- Animal Biometrics
Research output
- 1 Conference Paper
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Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending
Yang, X., Mirmehdi, M. & Burghardt, T., 2 Nov 2019. 8 p.Research output: Contribution to conference › Conference Paper › peer-review
Open AccessFile
Datasets
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PanAfrican2020
Sakib, F. (Contributor) & Burghardt, T. (Contributor), University of Bristol, 9 Jun 2021
DOI: 10.5523/bris.jh6hrovynjik2ix2h7m6fdea3, http://data.bris.ac.uk/data/dataset/jh6hrovynjik2ix2h7m6fdea3
Dataset
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