The study introduces an Event Recognition in Aerial video (ERA) dataset comprising 2,866 aerial videos collected from YouTube and annotated with labels from 25 different classes corresponding to an event that can be seen unfolding over a period of five seconds.
In collaboration with Partnership on AI, Microsoft, and academics from top universities, Facebook today announced the Deepfake Detection Challenge (DFDC) with the aim of finding innovative deepfake detection solutions to help the media industry spot videos that have been morphed by AI models.
Alphabet’s autonomous driving unit Waymo surprised many by releasing a new high-quality multimodal sensor dataset for autonomous driving. The *Waymo Open Dataset *was introduced at top AI conference Computer Vision and Pattern Recognition (CVPR) 2019 in Long Beach, California.
Google today announced the release of a new and improved landmark recognition dataset. Google-Landmarks-v2 includes over 5 million images, doubling the number in the landmark recognition dataset the tech giant released last year. The dataset now covers more than 200 thousand different landmarks, a seven times increase over the first version.
If we ask one of today’s AI-powered voice assistants like Alexa and Siri to tell a joke, it might very well come up with something that puts a smile on our face. If however we then asked “Why do you think that joke is funny?” the bot would be stuck for a response. AI researchers want to change that.
Chinese technology giant Tencent has open-sourced its face detection algorithm DSFD (Dual Shot Face Detector). The related paper DSFD: Dual Shot Face Detector achieves state-of-the-art performance on WIDER FACE and FDDB dataset benchmarks, and has been accepted by top computer vision conference CVPR 2019.
A collaboration between researchers from China’s Beihang University and Microsoft Research Asia has produced TableBank, a new image-based dataset for table detection and recognition built with novel weak supervision from Word and Latex documents on the Internet.
Chinese AI company iFLYTEK has bested the SQuAD2.0 challenge once again. The model “BERT + DAE + AoA” submitted by the joint iFLYTEK Research and HIT (Harbin Institute of Technology) laboratory HFL outperformed humans on both EM (exact match) and F1-score (fuzzy match) indexes to top the SQuAD2.0 leaderboard.
The San Francisco-based AI non-profit however has raised eyebrows in the research community with its unusual decision to not release the language model’s code and training dataset. In a statement sent to Synced, OpenAI explained the choice was made to prevent malicious use: “it’s clear that the ability to generate synthetic text that is conditioned on specific subjects has the potential for significant abuse.”
Uber has unveiled Ludwig, a new TensorFlow-based toolkit that enables users to train and test deep learning models without writing any code. The toolkit will help non-experts understand models and accelerate their iterative development by simplifying the prototyping process and data processing.
In December Synced reported on a hyperrealistic face generator developed by US chip giant NVIDIA. The GAN-based model performs so well that most people can’t distinguish the faces it generates from real photos. This week NVIDIA announced that it is open-sourcing the nifty tool, which it has dubbed “StyleGAN”.
The proliferation of social media in our daily lives has profoundly changed the way we work and play with others. It has also created an entirely new job: thousands of people worldwide now work for Google, Facebook and Twitter “Community Operations Teams.” Whenever a user flags content as offensive, it’s sent to these guys for review.
Facebook AI Research (FAIR) and the New York University (NYU) School of Medicine’s Center for Advanced Imaging Innovation and Research (CAI2R) announced today they are sharing a standardized set of AI tools and baselines and MRI data as part of their joint research project fastMRI.
If you’ve ever wondered whether Dota 2 or League of Legends is the most popular multiplayer online battle arena game, or how long you’d need to spend on a treadmill to burn off that party size bag of chips you just ate, you know that you can probably find the answer by accessing a couple of relevant information sources and then applying what seems like a natural and straightforward reasoning process.
Tencent AI Lab has announced an open-source NLP dataset comprising vector representations for eight million Chinese words and phrases. The dataset aims to provide large-scale and high-quality support for deep learning-based Chinese language NLP research in both academic and industrial applications.