New Google & Oxford Model Time-Shifts People in Videos
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.
Category: Computer Vision & Graphics
New DeepMind Approach ‘Bootstraps’ Self-Supervised Learning of Image Representations
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.
Argo AI Model Jointly Plots Vehicle Pose and Shape From LiDAR Data
Researchers have introduced a novel network architecture for jointly estimating the shape and pose of vehicles even from partial LiDAR observations.
Virginia Tech & Facebook Video Completion Algorithm Achieves SOTA Results
Researchers introduced a novel flow-based video completion algorithm that compares favourably with the state-of-the-art in the field.
IIIT Hyperbad’s ‘Wav2Lip’ Boosts Lip-Sync Video Performance
“Wav2Lip,” a novel lip-synchronization model that outperforms current approaches by a large margin in both quantitative metrics and human evaluations.
Microsoft Researcher Single-Handedly Surveys the SOTA in Sign Language Recognition
Researcher composes a quantitative survey of the SOTA in sign language recognition (SLR).
Intel Lab Transforms Your Phone into a Robot for $50
Intel Labs researchers have proposed a novel method for building a robot called “OpenBot” on just a US$50 budget.
Detecting Deepfakes: MIT CSAIL Model Identifies Manipulations Using Local Artifacts
Researchers proposed a new model that is designed to spot deepfakes by looking at subtle visual artifacts.
Fewer Cameras and Faster Processing: USC Proposes Monocular Real-Time Volumetric Performance Capture
A novel volumetric capture system that is capable of fully capturing clothed human bodies in real-time using only a single RGB webcam.
ECCV 2020 Best Paper Award Goes to Princeton Team
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.
CUHK & Facebook Demonstrate SOTA Monocular 3D Hand Motion Capture Method ‘FrankMocap’
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.
MRI Study Reveals Arterial Culprit Plaque Characteristics
Researchers developed a head-neck combined HR-MRVWI technique that could potentially provide remarkable suppression of cerebrospinal fluid signals.
Tesla Video Data Processing Supercomputer ‘Dojo’ – Building a 4D System Aiming at L5 Self-Driving
Elon Musk tweeted that Tesla is recruiting AI or chip talents for the company’s neural network training supercomputer project “Dojo.”
Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image Restoration
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.
Love-Love: Stanford Researchers Generate Realistic ‘Fake’ Wimbledon
A Stanford University research team has responded with an AI-powered model capable of realistically simulating a Wimbledon final and more.
SIAT Researchers Propose Effective Method for Skin Lesion Segmentation
Researchers proposed a novel and effective automatic segmentation method by using Generative Adversarial Networks with dual discriminators.
Introducing Holicity: A City-Scale Dataset for Learning Holistic 3D Structures
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.
Tour the World From Your Couch: Google ‘NeRF-W’ Delivers Accurate 3D Scene Reconstruction of Complex Outdoor Environments
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.
Eyes on Me: Google AI ‘MediaPipe Iris’ Improves Iris Tracking and Distance Estimation
MediaPipe Iris, a novel machine learning model designed to deliver accurate iris estimation without using depth sensors.
Pixel2Style2Pixel: Novel Encoder Architecture Boosts Facial Image-To-Image Translation
Researchers from Penta-AI and Tel-Aviv University introduce a generic image-to-image translation framework dubbed Pixel2Style2Pixel (pSp).
Unselfie Turns Arm-Extended Selfies into Neutral-Pose Portraits
“Unselfie,” a novel photographic transformation model that can automatically translate selfies into neutral-pose portraits.
AI Generator Learns to ‘Draw’ Like Cartoonist Lee Mal-Nyeon in Just 10 Hours
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.
Asia China Computer Vision & Graphics Health Machine Learning & Data Science Research Shenzhen Institute of Advanced Technology
About Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
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.
New White-Box Framework Will Cartoonize Your World
This framework can generate high-quality cartoonized images with much-improved controllability.
Adobe and Stanford Unveil SOTA Method for Human Pose Estimation
The researchers say the approach produces motions that are visually and physically much more plausible than state-of-the-art methods.
Medical Image Computation and the Application
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.
DeepMind’s AlignNet Learns Stable Object Representations Across Time
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.
Joint Spatial-Temporal Transformation Learning Boosts Video Inpainting Performance
Researchers introduce a joint Spatial-Temporal Transformer Network (STTN) to tackle such video inpainting challenges.
Facebook & Inria Propose High-Performance Self-Supervised Technique for CV Tasks
Researchers have developed a new technique for self-supervised training of convolutional networks used for image classification and other computer vision tasks.
Fujitsu Develops World’s First AI technology to Accurately Capture Characteristics of High-Dimensional Data Without Labeled Training Data
Fujitsu has developed the world’s first AI technology that accurately captures the characteristics of high-dimensional data without labeled training data.
Google Bridges Domain Gaps in Semantic Segmentation of LiDAR Point Clouds
A team of Google researchers recently proposed a novel “complete and label” domain adaptation approach.
NVIDIA Novel vid2vid Framework Synthesizes Realistic World-Consistent Videos
NVIDIA researchers propose a novel vid2vid framework that utilizes all past generated frames during rendering.
Grand Theft Auto Scene Context Data Boosts Human Motion Prediction
A team of researchers proposed a novel three-stage learning framework that includes scene context to generate long-term 3D human motion prediction when given a single scene image and 2D pose histories.
Novel Vision-based Algorithm to Track Pose of Spacecraft in Real Time
Researchers from the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences and their collaborators from Beihang University developed a novel vision-based algorithm to track the 6-DOF pose of a multi-rigid-body spacecraft in real time.
‘Beyond the ConvNet’ -Stanford & MIT Neural Network Learns Physical Graph Representations from Video
Researchers introduce a novel Physical Scene Graphs (PSG) approach designed to obtain a better structured understanding of visual scenes.
Facebook Introduces Integrated Eye & Face Model for 3D Immersion in Remote Communication
The proposed method generalizes well across various degrees of eye openness, different identities, and combinations of eye and lower facial expressions.
Stanford ‘SIRENs’ Apply Periodic Activation Functions to Implicit Neural Representations
The researchers introduce sinusoidal representation networks (SIRENs) as a method for leveraging periodic activation functions for implicit neural representations.
Fourier Feature Mapping Enables MLPs to Learn High-Frequency Functions in Low-Dimensional Domains
Researchers have proposed the use of Fourier feature mapping with MLPs in order to learn high-frequency functions in low-dimensional problem domains.
Local Motion Phases Technique Boosts Basketball Animation Richness and Realism
Researchers have proposed a novel framework that learns fast and dynamic character interactions.
CVPR 2020 Underway, Best Papers Announced
The 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) has announced its best paper awards.