The GOT-10k dataset contains more than 10,000 video segments of real-world moving objects and over 1.5 million manually labelled bounding boxes. The dataset contains more than 560 classes of real-world moving objects and 80+ classes of motion patterns.
204 PAPERS • 2 BENCHMARKS
VideoCube is a high-quality and large-scale benchmark to create a challenging real-world experimental environment for Global Instance Tracking (GIT). MGIT is a high-quality and multi-modal benchmark based on VideoCube-Tiny to fully represent the complex spatio-temporal and causal relationships coupled in longer narrative content.
5 PAPERS • NO BENCHMARKS YET
The evaluation of object detection models is usually performed by optimizing a single metric, e.g. mAP, on a fixed set of datasets, e.g. Microsoft COCO and Pascal VOC. Due to image retrieval and annotation costs, these datasets consist largely of images found on the web and do not represent many real-life domains that are being modelled in practice, e.g. satellite, microscopic and gaming, making it difficult to assert the degree of generalization learned by the model.
4 PAPERS • 1 BENCHMARK
BioDrone is the first bionic drone-based single object tracking benchmark, it features videos captured from a flapping-wing UAV system with a major camera shake due to its aerodynamics. BioDrone highlights the tracking of tiny targets with drastic changes between consecutive frames, providing a new robust vision benchmark for SOT. 1. Large-scale and high-quality benchmark with robust vision challenges 2. Rich challenging factor annotation 3. Videos from Bionic-based UAV 4. Tracking baselines with comprehensive experimental analyses
1 PAPER • NO BENCHMARKS YET
SOTVerse is a user-defined task space of single object tracking. It allows users to customize SOT tasks according to their research purposes, which on the one hand makes research more targeted, and on the other hand can significantly improve the efficiency of research.