AI Paper Summary

AI Researchers From UC San Diego Introduce A Method To Bypass Deepfake Detectors By Adversarially Modifying Fake Videos

The increasing circulation of fake videos through various platforms, primarily social media, has raised concerns worldwide, questioning digital media’s credibility. Adding to these concerns, scientists...

Researchers from the University of Sheffield & Beihang University Introduce a New Approach Based on Transfer Learning to Automate Historical Text Summarization

The researchers at the University of Sheffield, Beihang University, and Open University’s Knowledge Media Institute have introduced historical text summarization task, where documents in...

Researchers from InnoPeak Technology Propose GCF-Net: Gated Clip Fusion Network for Video Action Recognition

Researchers from InnoPeak Technology at Palo Alto, California, introduce Gated Clip Fusion Network (GCF-Net) to boost the existing video action classifiers with a tiny...

Taking Accessibility of Mobile Apps to the Next Level with IconNet, A Vision-Based Object Detection Model

Researchers at Google AI recently developed a technology called IconNet that enables Android users to have hands-free control over their mobile devices using voice...

Microsoft And The University Of California, Merced Introduces ZeRO-Offload, A Novel Heterogeneous DeepLearning Training Technology To Train Multi-Billion Parameter Models On A Single GPU

We are progressing towards an era of technology that is becoming heavily dependent on Deep Learning (DL) models. As these models' size increases exponentially, it...

Researchers At NAVER AI Lab Introduces ReLabel: A Novel Framework To Turn ImageNet Evaluation Into A Multi-Label Task

ImageNet is one of the most popular image classification benchmarks. It contains more than 14 million labeled images and has improved many image recognition...

Stanford Researchers Introduces ArtEmis, A Dataset Containing 439K Emotion Attributions

ArtEmis, described as the Affective Language for Visual Art, is a novel large-scale dataset and its accompanying ML models to provide a detailed understanding...

Google Researchers Introduce a New Framework (TReCS) For Text-to-Image Generation

Deep neural networks based on Generative Adversarial Networks (GANs) have facilitated end-to-end trainable photo-realistic text-to-image generation. Many methods also use intermediate scene graph representations...

Google Trains A Trillion-Parameter AI Language Model That Is Almost 6 Times Bigger Than GPT-3

Google researchers have developed techniques that can now train a language model with more than a trillion parameters. The 1.6 trillion parameter model is the...

Researchers From Computer Vision Center (CVC) And The University Of Barcelona Conducted A Study That Results In Improved Accuracy On Face Verification Tasks In...

Automatic face recognition is being widely adopted by private and governmental organizations worldwide for various legitimate and beneficial purposes, such as improving security. However,...

OpenAI Introduces CLIP: A Neural Network That Efficiently Learns Visual Concepts From Natural Language Supervision

OpenAI introduced a neural network, CLIP, which efficiently learns visual concepts from natural language supervision. CLIP, also called Contrastive Language–Image Pre-training, is available to be...

Max Planck Institute and Facebook Reality Labs Develop A Model That Performs Human Re-Rendering From A Single Image

A team of researchers from the Max Planck Institute for Informatics and Facebook Reality Labs has developed an end to end trainable technique that performs human re-rendering from...

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