However, the state-of-the-art architectures on small scale datasets are frequently impractical to deploy at internet scale, both in terms of the ability to train such deep networks on hundreds of millions of videos, and to deploy them for inference on billions of videos. In this paper, we ...
The task of this study is the recognition of emotional reactions in videos. For this research, the Hume-Reaction dataset, a large-scale, multimodal dataset designed explicitly for the Emotional Reactions Sub-Challenge (MuSe-Reaction) [5], was employed. The dataset is notable for its extensive ...
Evolutionary-Scale Prediction of Atomic-Level Protein Structure with a Language Model. Science 2023, 379, 1123–1130. [Google Scholar] [CrossRef] Hu, Y.-H.; Fu, J.S.; Yeh, H.-C. Developing an Early-Warning System through Robotic Process Automation: Are Intelligent Tutoring Robots as ...
It includes short- (< 2min), medium- (4min~15min), and long-term (30min~60min) videos, ranging from11 seconds to 1 hour. All data are newly collected and annotated by humans, not from any existing video dataset. ✨ 🔥🔥🔥MME: A Comprehensive Evaluation Benchmark for Multimodal ...
Clip-level scale optimization achieves the highest performance. Source data are provided as a Source Data file. Full size image When evaluated on the challenge set, the models trained in the small-scale regime (Fig. 3g, h) performed poorly (e.g., a model trained on 1000 images from the ...
Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-train
The videos on YouTube might also exhibit potential biases: 1) Over-representation of some behaviors and under- 6. Conclusion We introduced MammalNet, a large-scale video dataset for mammal recognition and behavior understanding. We have collected videos for hundreds ...
Although large-scale datasets exist for image understanding, such as ImageNet, there are no comparable size video classification datasets. In this paper, we introduce YouTube-8M, the largest multi-label video classification dataset, composed of ~8 million videos (500K hours of video), annotated ...
To scale up the study of attribute bias, we leverage the dataset generated by AttrPrompt as a probe. In particular, we employ the attributes associated with each data of AttrPrompt to train an attribute classifier, which is in turn used to make attribute predictions on Gold and SimPrompt dat...
In fact, there are several projects that use LiDAR systems for infrastructure documentation at large scales, such as transportation/power lines mapping and monitoring and inspection on large areas, possibly up to national scale. Moreover, some recent applications, such as autonomous/assisted driving,...