n the new paper Adversarial Examples Are Not Bugs, They Are Features, a group of MIT researchers propose that adversarial examples’ effectiveness can be attributed to non-robustness: “Adversarial vulnerability is a direct result of our models’ sensitivity to well-generalizing features in the data.”
Current state-of-the-art convolutional architectures for object detection tasks are human-designed. In a recent paper, Google Brain researchers leveraged the advantages of Neural Architecture Search (NAS) to propose NAS-FPN, a new automatic search method for feature pyramid architecture.
Traditional methods used to estimate 3D structure and camera motion in videos rely heavily on manual assumptions such as continuity and planarity. Google researchers have now presented an alternative deep learning method which is able to obtain these assumptions from unlabelled video.
The Seventh International Conference on Learning Representations (ICLR) kicked off today. One of the world’s major machine learning conferences, ICLR this year received 1591 main conference paper submissions — up 60 percent over last year — and accepted 24 for oral presentations and 476 as poster presentations.
Designing accurate and efficient CNNs for mobile devices is challenging due to the large design space and expensive computational methods. Although many mobile CNNs are available for developers to train and deploy to mobile devices, existing CNN architecture may not be able to achieve the best results for some tasks on mobile devices.
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.
“AI is the best bot to keep people safe on our platforms,” Facebook Director of Artificial Intelligence Manohar Paluri told the F8 audience, adding that an effective way to achieve that goal is enabling Facebook’s AI system to “understand content and work effectively with less labeled training data.”
A group of Google researchers led by Quoc Le — the AI expert behind Google Neural Machine Translation and AutoML — have published a paper proposing attention augmentation. In experiment results, the novel two-dimensional relative self-attention mechanismfor image classification delivers “consistent improvements in image classification.”
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.
Advanced machine learning techniques and the widespread deployment of surveillance cameras have dramatically improved the efficiency and accuracy of human detection systems in airports, train stations, and other sensitive public places. Is this the end of anonymity?
Thanks to the CUDA architecture  developed by NVIDIA, developers can exploit GPUs’ parallel computing power to perform general computation without extra efforts. Our objective is to evaluate the performance achieved by TensorFlow, PyTorch, and MXNet on Titan RTX.
Researchers from Facebook, the National University of Singapore, and the Qihoo 360 AI Institute have jointly proposed OctConv (Octave Convolution), a promising new alternative to traditional convolution operations. Akin to a “compressor” for Convolutional Neural Networks (CNN), the OctConv method saves computational resources while boosting effectiveness.
Interactive movies are redefining cinema and storytelling and opening up a world of possibilities in the entertainment industry. There are no “spoilers” for films with no predetermined endings, whose characters and plots develop based on viewers’ real-time direction. Now, what if these viewers became characters?
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.
As robots take over industrial manufacturing, specific and accurate robot control is becoming more important. Conventional feedback control methods can effectively solve various types of robot control problems by capturing structures with explicit models such as motion equations.