Google, Stanford, & MIT Top NeurIPS 2020 Accepted Papers List
NeurIPS 2020 released its list of accepted papers this week with Google, Stanford, and MIT as the top affiliations.
AI Technology & Industry Review
NeurIPS 2020 released its list of accepted papers this week with Google, Stanford, and MIT as the top affiliations.
Google AI researchers developed a sign language detection model for video conferencing applications that can perform real-time identification of a person signing as an active speaker.
Google AI has announced a new audiovisual speech enhancement feature in YouTube Stories (iOS) that enables creators to make better selfie videos by automatically enhancing their voices and reducing noise.
Novel model uses a quality estimator and evolutionary optimization to search the latent space of GANs trained on limited datasets.
Imaginaire, a universal PyTorch library designed for various GAN-based tasks and methods.
Chinese researchers propose a novel regression framework in pursuit of “fast, accurate and stable 3D dense face alignment simultaneously.”
VR and AR will converge to combine the real and virtual, as Facebook Reality Labs researchers, developers, and engineers aim to change how we see the world.
Synced has identified a few significant technical advancements in the 3D photo field that we believe may be of interest to our readers.
UIUC, Adobe Research and University of Oregon propose HDMatt, a Deep Learning-based image matting Cross-Patch Context module for high-resolution image inputs.
A group of researchers from Google Research and the University of Oxford have introduced a novel technique that can “retiming” people’s movements in videos.
From an augmented view of an image, the researchers trained the online network to predict the target network representation of the same image under a different augmented view.
Researchers have introduced a novel network architecture for jointly estimating the shape and pose of vehicles even from partial LiDAR observations.
Researchers introduced a novel flow-based video completion algorithm that compares favourably with the state-of-the-art in the field.
“Wav2Lip,” a novel lip-synchronization model that outperforms current approaches by a large margin in both quantitative metrics and human evaluations.
Researcher composes a quantitative survey of the SOTA in sign language recognition (SLR).
Intel Labs researchers have proposed a novel method for building a robot called “OpenBot” on just a US$50 budget.
Researchers proposed a new model that is designed to spot deepfakes by looking at subtle visual artifacts.
A novel volumetric capture system that is capable of fully capturing clothed human bodies in real-time using only a single RGB webcam.
The 16th European Conference on Computer Vision (ECCV) kicked off on Sunday as a fully online conference. In the Conference Opening Session this morning, the ECCV organizing committee announced the conference’s paper submission stats and Best Paper selections.
Researchers from The Chinese University of Hong Kong, Facebook Reality Labs, and Facebook AI Research have unveiled a state-of-the-art monocular 3D hand motion capture method, FrankMocap, which can estimate both 3D hand and body motions from in-the-wild monocular inputs with faster speed and better accuracy than previous approaches.
Researchers developed a head-neck combined HR-MRVWI technique that could potentially provide remarkable suppression of cerebrospinal fluid signals.
Elon Musk tweeted that Tesla is recruiting AI or chip talents for the company’s neural network training supercomputer project “Dojo.”
To adapt conventional deep models to real scenarios, a research work carried by a team (XPixel) from the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences investigated the use of additional branches to tune imagery effects.
A Stanford University research team has responded with an AI-powered model capable of realistically simulating a Wimbledon final and more.
Researchers proposed a novel and effective automatic segmentation method by using Generative Adversarial Networks with dual discriminators.
HoliCity, a city-scale dataset and all-in-one data platform for research into learning abstracted high-level holistic 3D structures derived from city CAD (computer-aided design) models.
Google researchers have introduced a series of extensions to the SOTA view-synthesis method Neural Radiance Fields (NeRF) that enable it to produce high-quality 3D representations of complex scenes with only unstructured image collections as input.
MediaPipe Iris, a novel machine learning model designed to deliver accurate iris estimation without using depth sensors.
Researchers from Penta-AI and Tel-Aviv University introduce a generic image-to-image translation framework dubbed Pixel2Style2Pixel (pSp).
“Unselfie,” a novel photographic transformation model that can automatically translate selfies into neutral-pose portraits.
A Seoul National University Master’s student and developer has trained a face generating model to transfer normal face photographs into cartoon images in the distinctive style of Lee Mal-nyeon.
SIAT aims to enhance the innovative capacity of the equipment manufacturing and service industries in the Guangdong-Hong Kong region, promote the development of emerging industries possessing their own proprietary intellectual property, and become a world-class industrial research institute.
This framework can generate high-quality cartoonized images with much-improved controllability.
The researchers say the approach produces motions that are visually and physically much more plausible than state-of-the-art methods.
The process of applying machine learning methods in medical image analysis is called medical image computation. This post will introduce SIAT’s work in medical image synthesis, classification, and segmentation.
New research from UK based AI company and research lab DeepMind is enabling AI agents to perceive dynamic real-world environments more like humans do.
Researchers introduce a joint Spatial-Temporal Transformer Network (STTN) to tackle such video inpainting challenges.
Researchers have developed a new technique for self-supervised training of convolutional networks used for image classification and other computer vision tasks.
Fujitsu has developed the world’s first AI technology that accurately captures the characteristics of high-dimensional data without labeled training data.
A team of Google researchers recently proposed a novel “complete and label” domain adaptation approach.