The original Moving Camouflaged Animals (MoCA) Dataset includes 37K frames from 141 YouTube Video sequences with resolution and sampling rate of 720 × 1280 and 24fps in the majority of cases. The dataset covers 67 types of animals moving in natural scenes, but some are not camouflaged animals. Also, the ground truth of the original dataset is bounding boxes rather than dense segmentation masks, which makes it hard to evaluate the VCOD segmentation performance. To this end, we reorganize the dataset as MoCA-Mask and build a comprehensive benchmark with more comprehensive evaluation criteria.
7 PAPERS • 1 BENCHMARK
The nine (moving camera) videos in this benchmark exhibit camouflaged animals that are difficult to see in a single frame, but can be detected based upon their motion across frames.
4 PAPERS • 1 BENCHMARK