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FASTTEXT - FACEBOOK
FastText is a lightweight library designed to help build scalable solutions for text representation and classification. It works on standard, generic hardware and can even fit on smartphones and small computers through functionality that reduces memory consumed byfastText models.
CASUAL CONVERSATIONS DATASET Overview. Casual Conversations is composed of over 45,000 videos (3,011 participants) and intended to be used for assessing the performance of already trained models in computer vision and audio applications for the purposes permitted in our data user agreement.The videos feature paid individuals who agreed to participate in the project and explicitly provided age and gender labels FACEBOOK AI’S RAISE PROGRAM: A NEW PATHWAY TO MAKE CAREERS Careers in AI should be open to everyone with the curiosity to make an impact in this rapidly evolving field. With that in mind and to build a new path into the field, we’re launching RAISE (Rotational AI Science & Engineering), a 24-month program for experienced engineersfrom a
DETECTRON - FACEBOOK Detectron can be used out-of-the-box for general object detection or modified to train and run inference on your own datasets. It's written in Python and will be powered by HOW FACEBOOK USES SUPER-EFFICIENT AI MODELS TO DETECT HATE Earlier this year, we published our research on Linformer and released our code so other researchers and engineers could improve their models. Since our Facebook AI Research (FAIR) lab was founded in 2013, we’ve committed to an open science–based approach.Our research model revolves around publishing code and methodologies, collaborating with other researchers across industry and DYNABENCH - FACEBOOK DynaBench is a research platform for dynamic data collection and benchmarking. Static benchmarks have well-known issues: they saturate quickly, are susceptible to overfitting, contain exploitable annotator artifacts and have unclear or imperfect evaluation metrics. POWERED BY AI: TURNING ANY 2D PHOTO INTO 3D USING Our 3D Photos feature on Facebook launched in 2018 as a new, immersive format for sharing pictures with friends and family. The feature has relied on the dual-lens “portrait mode” capabilities available only in new, higher-end smartphones, however. So it hasn’t been available on typical mobile devices, which have only a single,rear-facing camera.
SELF-SUPERVISED LEARNING: THE DARK MATTER OF INTELLIGENCE Training an EBM consists of two parts: (1) showing it examples of x and y that are compatible and training it to produce a low energy, and (2) finding a way to ensure that for a particular x, the y values that are incompatible with x produce a higher energy than the FINDING AND FIXING SOFTWARE BUGS AUTOMATICALLY WITH SAPFIX To address high-firing bugs, SapFix creates patches that either fully or partially revert the code submission that introduced them. For more complex crashes, the system generates patches by drawing from its collection of templated fixes. DINO AND PAWS: ADVANCING THE STATE OF THE ART IN COMPUTER Many of the most exciting new AI breakthroughs have come from two recent innovations: self-supervised learning, which allows machines to learn from random, unlabeled examples; and Transformers, which enable AI models to selectively focus on certain parts of their input and thus reason more effectively.Both methods have been a sustained focus for Facebook AI, and we’re pleased toFASTTEXT - FACEBOOK
FastText is a lightweight library designed to help build scalable solutions for text representation and classification. It works on standard, generic hardware and can even fit on smartphones and small computers through functionality that reduces memory consumed byfastText models.
CASUAL CONVERSATIONS DATASET Overview. Casual Conversations is composed of over 45,000 videos (3,011 participants) and intended to be used for assessing the performance of already trained models in computer vision and audio applications for the purposes permitted in our data user agreement.The videos feature paid individuals who agreed to participate in the project and explicitly provided age and gender labels FACEBOOK AI’S RAISE PROGRAM: A NEW PATHWAY TO MAKE CAREERS Careers in AI should be open to everyone with the curiosity to make an impact in this rapidly evolving field. With that in mind and to build a new path into the field, we’re launching RAISE (Rotational AI Science & Engineering), a 24-month program for experienced engineersfrom a
DETECTRON - FACEBOOK Detectron can be used out-of-the-box for general object detection or modified to train and run inference on your own datasets. It's written in Python and will be powered by HOW FACEBOOK USES SUPER-EFFICIENT AI MODELS TO DETECT HATE Earlier this year, we published our research on Linformer and released our code so other researchers and engineers could improve their models. Since our Facebook AI Research (FAIR) lab was founded in 2013, we’ve committed to an open science–based approach.Our research model revolves around publishing code and methodologies, collaborating with other researchers across industry and DYNABENCH - FACEBOOK DynaBench is a research platform for dynamic data collection and benchmarking. Static benchmarks have well-known issues: they saturate quickly, are susceptible to overfitting, contain exploitable annotator artifacts and have unclear or imperfect evaluation metrics. POWERED BY AI: TURNING ANY 2D PHOTO INTO 3D USING Our 3D Photos feature on Facebook launched in 2018 as a new, immersive format for sharing pictures with friends and family. The feature has relied on the dual-lens “portrait mode” capabilities available only in new, higher-end smartphones, however. So it hasn’t been available on typical mobile devices, which have only a single,rear-facing camera.
SELF-SUPERVISED LEARNING: THE DARK MATTER OF INTELLIGENCE Training an EBM consists of two parts: (1) showing it examples of x and y that are compatible and training it to produce a low energy, and (2) finding a way to ensure that for a particular x, the y values that are incompatible with x produce a higher energy than the FINDING AND FIXING SOFTWARE BUGS AUTOMATICALLY WITH SAPFIX To address high-firing bugs, SapFix creates patches that either fully or partially revert the code submission that introduced them. For more complex crashes, the system generates patches by drawing from its collection of templated fixes. AI CAN NOW EMULATE TEXT STYLE IN IMAGES IN ONE SHOT By openly publishing this research, we hope to spur additional research and dialogue preempting deepfake text attacks in the same way that we do with deepfake faces.If AI researchers and practitioners can get ahead of adversaries in building this technology, we can learn to better detect this new style of deepfakes and build robust systems tocombat them.
HOW FACEBOOK USES SUPER-EFFICIENT AI MODELS TO DETECT HATE Earlier this year, we published our research on Linformer and released our code so other researchers and engineers could improve their models. Since our Facebook AI Research (FAIR) lab was founded in 2013, we’ve committed to an open science–based approach.Our research model revolves around publishing code and methodologies, collaborating with other researchers across industry and TEXTSTYLEBRUSH: TRANSFER OF TEXT AESTHETICS FROM A SINGLE Abstract. We present a novel approach for disentangling the content of a text image from all aspects of its appearance. The appearance representation we derive can then be applied to new content, for one-shot transfer of the source style to new content. LAUNCHING THE NETHACK CHALLENGE AT NEURIPS 2021 Challenges for the state of the art of RL run rife in NetHack: Partial observation makes exploration essential.Procedural generation and “permadeath” make the cost of failure significant. Agents cannot reset or interfere with the environment, making methods like Monte Carlo Tree Search (underpinning agents such as AlphaZero for StarCraft II or GoExplore for Montezuma’s Revenge) LIVE FACE DE-IDENTIFICATION IN VIDEO Abstract. We propose a method for face de-identification that enables fully automatic video modification at high frame rates. The goal is to maximally decorrelate the identity, while having the perception (pose, illumination and expression) fixed. TIMESFORMER: A NEW ARCHITECTURE FOR VIDEO UNDERSTANDING The figure provides a visualization of the self-attention heatmaps learned by TimeSformer. The first row shows the original frames, while the second row weights the color of each pixel by the importance given by self-attention for the classification of DETECTRON - FACEBOOK Detectron can be used out-of-the-box for general object detection or modified to train and run inference on your own datasets. It's written in Python and will be powered by PYTORCHVIDEO: A DEEP LEARNING LIBRARY FOR VIDEO UNDERSTANDING What it is: PyTorchVideo is a deep learning library for research and applications in video understanding. It provides easy-to-use, efficient, and reproducible implementations of state-of-the-art video models, data sets, transforms, and tools in PyTorch. SELF-SUPERVISED LEARNING: THE DARK MATTER OF INTELLIGENCE Training an EBM consists of two parts: (1) showing it examples of x and y that are compatible and training it to produce a low energy, and (2) finding a way to ensure that for a particular x, the y values that are incompatible with x produce a higher energy than the HOW FACEBOOK ANNOTATES MULTIMODAL TRAINING DATA FOR ML We have built an annotation platform that allows Facebook researchers to more easily and efficiently create high-quality training data.FACEBOOK AI TOOLS
To enable speech recognition technology for many more languages spoken around the globe, Facebook AI is releasing wav2vec Unsupervised, a new method to train models with no supervision whatsoever. Wav2vec Unsupervised rivals the performance of the best DYNABENCH - AI.FACEBOOK.COM DynaBench is a research platform for dynamic data collection and benchmarking. Static benchmarks have well-known issues: they saturate quickly, are susceptible to overfitting, contain exploitable annotator artifacts and have unclear or imperfect evaluation metrics. Learn More. Read the Paper. DINO AND PAWS: ADVANCING THE STATE OF THE ART IN COMPUTER When pretraining a standard ResNet-50 model with PAWS using just 1 percent of the labels in ImageNet, we get state-of-the-art accuracy while doing 10x fewer pretraining steps. With DINO and PAWS, the AI research community can build new computer vision systems that are far less dependent on labeled data and vast computing resources fortraining.
2021 HABITAT CHALLENGE LAUNCHES TO ADVANCE EMBODIED AI Facebook AI is excited to launch the third Habitat Challenge, an open research initiative that invites AI experts around the world to teach machines to navigate through real-world environments. Participants will train embodied agents to perform PointGoal and ObjectGoal navigation using Habitat-Sim, Facebook AI’s flexible, high-performance open source 3D simulator. FACEBOOK AI’S RAISE PROGRAM: A NEW PATHWAY TO MAKE CAREERS To provide an alternative path into AI, Facebook is launching Rotational AI Science & Engineering (RAISE). RAISE is a 24-month program offering participants full-time employment with the Facebook AI team. It is designed to bring a cohort of software engineers together from a variety of industry experiences and backgrounds --ranging from
PYTORCHVIDEO: A DEEP LEARNING LIBRARY FOR VIDEO UNDERSTANDING What it is: PyTorchVideo is a deep learning library for research and applications in video understanding. It provides easy-to-use, efficient, and reproducible implementations of state-of-the-art video models, data sets, transforms, and tools in PyTorch. HOW FACEBOOK ANNOTATES MULTIMODAL TRAINING DATA FOR ML How Facebook annotates multimodal training data for ML. We have built an annotation platform called Halo, which allows Facebook researchers to more easily and efficiently create high-quality training data. Halo creates annotation tasks and then visualizes corresponding data across diverse media types, including images, audio, video, and 3D. COVOST V2: EXPANDING THE LARGEST, MOST DIVERSE CoVoST V2 will facilitate translating 21 languages into English, as well as English into 15 languages. In order to support wider research and applications in multilingual speech translation, we have released CoVoST V2 as free to use via a Creative Commons (CC0) license. Developed in 2019, the initial version of CoVoST used Mozilla’s open JEFF SMITH - AI.FACEBOOK.COM Jeff Smith is a Research Engineering Manager in FAIR. His work spans core learning methods, deep learning frameworks, and reproducibility. FINDING AND FIXING SOFTWARE BUGS AUTOMATICALLY WITH SAPFIX SapFix is designed to operate as an independent tool, able to run either with or without Sapienz, Facebook’s intelligent automated software testing tool, which was announced at F8 and has already been deployed to production. In its current, proof-of-concept state, SapFix is focused on fixing bugs found by Sapienz before they reachproduction.
FACEBOOK AI TOOLS
To enable speech recognition technology for many more languages spoken around the globe, Facebook AI is releasing wav2vec Unsupervised, a new method to train models with no supervision whatsoever. Wav2vec Unsupervised rivals the performance of the best DYNABENCH - AI.FACEBOOK.COM DynaBench is a research platform for dynamic data collection and benchmarking. Static benchmarks have well-known issues: they saturate quickly, are susceptible to overfitting, contain exploitable annotator artifacts and have unclear or imperfect evaluation metrics. Learn More. Read the Paper. DINO AND PAWS: ADVANCING THE STATE OF THE ART IN COMPUTER When pretraining a standard ResNet-50 model with PAWS using just 1 percent of the labels in ImageNet, we get state-of-the-art accuracy while doing 10x fewer pretraining steps. With DINO and PAWS, the AI research community can build new computer vision systems that are far less dependent on labeled data and vast computing resources fortraining.
2021 HABITAT CHALLENGE LAUNCHES TO ADVANCE EMBODIED AI Facebook AI is excited to launch the third Habitat Challenge, an open research initiative that invites AI experts around the world to teach machines to navigate through real-world environments. Participants will train embodied agents to perform PointGoal and ObjectGoal navigation using Habitat-Sim, Facebook AI’s flexible, high-performance open source 3D simulator. FACEBOOK AI’S RAISE PROGRAM: A NEW PATHWAY TO MAKE CAREERS To provide an alternative path into AI, Facebook is launching Rotational AI Science & Engineering (RAISE). RAISE is a 24-month program offering participants full-time employment with the Facebook AI team. It is designed to bring a cohort of software engineers together from a variety of industry experiences and backgrounds --ranging from
PYTORCHVIDEO: A DEEP LEARNING LIBRARY FOR VIDEO UNDERSTANDING What it is: PyTorchVideo is a deep learning library for research and applications in video understanding. It provides easy-to-use, efficient, and reproducible implementations of state-of-the-art video models, data sets, transforms, and tools in PyTorch. HOW FACEBOOK ANNOTATES MULTIMODAL TRAINING DATA FOR ML How Facebook annotates multimodal training data for ML. We have built an annotation platform called Halo, which allows Facebook researchers to more easily and efficiently create high-quality training data. Halo creates annotation tasks and then visualizes corresponding data across diverse media types, including images, audio, video, and 3D. COVOST V2: EXPANDING THE LARGEST, MOST DIVERSE CoVoST V2 will facilitate translating 21 languages into English, as well as English into 15 languages. In order to support wider research and applications in multilingual speech translation, we have released CoVoST V2 as free to use via a Creative Commons (CC0) license. Developed in 2019, the initial version of CoVoST used Mozilla’s open JEFF SMITH - AI.FACEBOOK.COM Jeff Smith is a Research Engineering Manager in FAIR. His work spans core learning methods, deep learning frameworks, and reproducibility. FINDING AND FIXING SOFTWARE BUGS AUTOMATICALLY WITH SAPFIX SapFix is designed to operate as an independent tool, able to run either with or without Sapienz, Facebook’s intelligent automated software testing tool, which was announced at F8 and has already been deployed to production. In its current, proof-of-concept state, SapFix is focused on fixing bugs found by Sapienz before they reachproduction.
PYTORCH BUILDS THE FUTURE OF AI AND MACHINE LEARNING AT Bridging the research-to-production gap. Historically, AI’s research-to-production pipeline has been tedious and complicated. Multiple steps and tools, fragmented processes, and lack of any clear standardization across the AI industry made it nearly impossible to manage the end-to-end workflow. HOW FACEBOOK USES SUPER-EFFICIENT AI MODELS TO DETECT HATE Earlier this year, we published our research on Linformer and released our code so other researchers and engineers could improve their models. Since our Facebook AI Research (FAIR) lab was founded in 2013, we’ve committed to an open science–based approach.Our research model revolves around publishing code and methodologies, collaborating with other researchers across industry and ROTATIONAL AI SCIENCE & ENGINEERING Rotational AI Science & Engineering (RAISE) RAISE is a 24-month rotational program offering participants full-time employment with the Facebook AI team. It is designed to bring a cohort of software engineers together from a wide range of industry experiences and backgrounds -- ranging from individual contributors a few years out ofschool to
THE FLORES-101 DATA SET: HELPING BUILD BETTER TRANSLATION Today we are open-sourcing FLORES-101, a first-of-its-kind, many-to-many evaluation data set covering 101 languages (10,100 translation directions) from all over the world. TIMESFORMER: A NEW ARCHITECTURE FOR VIDEO UNDERSTANDING Facebook AI has built and is now sharing details about TimeSformer, an entirely new architecture for video understanding. It is the first video architecture that’s based purely on Transformers, which in recent years have become the dominant approach for many applications in natural language processing (NLP), including machine translationand
POWERED BY AI: TURNING ANY 2D PHOTO INTO 3D USING Powered by AI: Turning any 2D photo into 3D using convolutional neural nets. Our 3D Photos feature on Facebook launched in 2018 as a new, immersive format for sharing pictures with friends and family. The feature has relied on the dual-lens “portrait mode” capabilities available only in new, higher-end smartphones, however. CASUAL CONVERSATIONS DATASET Casual Conversations Dataset. Casual Conversations dataset is designed to help researchers evaluate their computer vision and audio models for accuracy across a diverse set of age, genders, apparent skin tones and ambient lighting conditions. Download the Dataset. Download the Paper. Read the Article. A STATE-OF-THE-ART OPEN SOURCE CHATBOT A state-of-the-art open source chatbot. Facebook AI has built and open-sourced BlenderBot, the largest-ever open-domain chatbot. It outperforms others in terms of engagement and also feels more human, according to human evaluators. The culmination of years of research in conversational AI, this is the first chatbot to blend a diverse set of LIVE FACE DE-IDENTIFICATION IN VIDEO Abstract. We propose a method for face de-identification that enables fully automatic video modification at high frame rates. The goal is to maximally decorrelate the identity, while having the perception (pose, illumination and expression) fixed. We achieve this by a novel feed-forward encoder-decoder network architecture that is conditioned NOT ALL MEMORIES ARE CREATED EQUAL: LEARNING TO FORGET BY We propose Expire-Span, a method that learns to retain the most important information and expire the irrelevant information. This forgetting of memories enables Transformers to scale to attend over tens of thousands of previous timesteps efficiently, as not all states from previous timesteps are preserved. We demonstrate that Expire-Spancan
FACEBOOK AI TOOLS
To enable speech recognition technology for many more languages spoken around the globe, Facebook AI is releasing wav2vec Unsupervised, a new method to train models with no supervision whatsoever. Wav2vec Unsupervised rivals the performance of the best DYNABENCH - AI.FACEBOOK.COM DynaBench is a research platform for dynamic data collection and benchmarking. Static benchmarks have well-known issues: they saturate quickly, are susceptible to overfitting, contain exploitable annotator artifacts and have unclear or imperfect evaluation metrics. Learn More. Read the Paper. AI GETS BETTER EVERY DAY. HERE’S WHAT THAT MEANS FOR AI gets better every day. Here’s what that means for stopping hate speech. The numbers Facebook released today in our latest Community Standards Enforcement Report are evidence of the many ways technology is delivering the kind of progress our world demands. In the final three months of 2020, we did better than ever before to proactively DETECTRON - FACEBOOK Rapid, flexible research. Detectron was built by Facebook AI Research (FAIR) to support rapid implementation and evaluation of novel computer vision research. It includes implementations for the following object detection algorithms: Detectron can be used out-of-the-box for general object detection or modified to train and run inference on your FACEBOOK AI’S RAISE PROGRAM: A NEW PATHWAY TO MAKE CAREERS To provide an alternative path into AI, Facebook is launching Rotational AI Science & Engineering (RAISE). RAISE is a 24-month program offering participants full-time employment with the Facebook AI team. It is designed to bring a cohort of software engineers together from a variety of industry experiences and backgrounds --ranging from
POWERED BY AI: TURNING ANY 2D PHOTO INTO 3D USINGDOWNLOAD A 3D MODELEXPLAIN 3D PRINTINGMAKE A 3D MODEL Powered by AI: Turning any 2D photo into 3D using convolutional neural nets. Our 3D Photos feature on Facebook launched in 2018 as a new, immersive format for sharing pictures with friends and family. The feature has relied on the dual-lens “portrait mode” capabilities available only in new, higher-end smartphones, however. UNSUPERVISED SPEECH RECOGNITION This paper describes wav2vec-U, short for wav2vec Unsupervised, a method to train speech recognition models without any labeled data. We leverage self-supervised speech representations to segment unlabeled audio and learn a mapping from these representations to phonemes via adversarial training. The right representations are key to the success FINDING AND FIXING SOFTWARE BUGS AUTOMATICALLY WITH SAPFIX SapFix is designed to operate as an independent tool, able to run either with or without Sapienz, Facebook’s intelligent automated software testing tool, which was announced at F8 and has already been deployed to production. In its current, proof-of-concept state, SapFix is focused on fixing bugs found by Sapienz before they reachproduction.
OPEN-SOURCING HYPERPARAMETER AUTOTUNING FOR FASTTEXT Hyperparameter autotuning, a new feature for our fastText library. This feature automatically determines the best hyperparameters for your dataset in order to build an efficient text classifier. To use autotuning, a researcher inputs the training data as well as a validation set and a time constraint. FastText then uses the allottedtime to
AROMA: USING ML FOR CODE RECOMMENDATIONFACEBOOK AI TOOLS
To enable speech recognition technology for many more languages spoken around the globe, Facebook AI is releasing wav2vec Unsupervised, a new method to train models with no supervision whatsoever. Wav2vec Unsupervised rivals the performance of the best DYNABENCH - AI.FACEBOOK.COM DynaBench is a research platform for dynamic data collection and benchmarking. Static benchmarks have well-known issues: they saturate quickly, are susceptible to overfitting, contain exploitable annotator artifacts and have unclear or imperfect evaluation metrics. Learn More. Read the Paper. AI GETS BETTER EVERY DAY. HERE’S WHAT THAT MEANS FOR AI gets better every day. Here’s what that means for stopping hate speech. The numbers Facebook released today in our latest Community Standards Enforcement Report are evidence of the many ways technology is delivering the kind of progress our world demands. In the final three months of 2020, we did better than ever before to proactively DETECTRON - FACEBOOK Rapid, flexible research. Detectron was built by Facebook AI Research (FAIR) to support rapid implementation and evaluation of novel computer vision research. It includes implementations for the following object detection algorithms: Detectron can be used out-of-the-box for general object detection or modified to train and run inference on your FACEBOOK AI’S RAISE PROGRAM: A NEW PATHWAY TO MAKE CAREERS To provide an alternative path into AI, Facebook is launching Rotational AI Science & Engineering (RAISE). RAISE is a 24-month program offering participants full-time employment with the Facebook AI team. It is designed to bring a cohort of software engineers together from a variety of industry experiences and backgrounds --ranging from
POWERED BY AI: TURNING ANY 2D PHOTO INTO 3D USINGDOWNLOAD A 3D MODELEXPLAIN 3D PRINTINGMAKE A 3D MODEL Powered by AI: Turning any 2D photo into 3D using convolutional neural nets. Our 3D Photos feature on Facebook launched in 2018 as a new, immersive format for sharing pictures with friends and family. The feature has relied on the dual-lens “portrait mode” capabilities available only in new, higher-end smartphones, however. UNSUPERVISED SPEECH RECOGNITION This paper describes wav2vec-U, short for wav2vec Unsupervised, a method to train speech recognition models without any labeled data. We leverage self-supervised speech representations to segment unlabeled audio and learn a mapping from these representations to phonemes via adversarial training. The right representations are key to the success FINDING AND FIXING SOFTWARE BUGS AUTOMATICALLY WITH SAPFIX SapFix is designed to operate as an independent tool, able to run either with or without Sapienz, Facebook’s intelligent automated software testing tool, which was announced at F8 and has already been deployed to production. In its current, proof-of-concept state, SapFix is focused on fixing bugs found by Sapienz before they reachproduction.
OPEN-SOURCING HYPERPARAMETER AUTOTUNING FOR FASTTEXT Hyperparameter autotuning, a new feature for our fastText library. This feature automatically determines the best hyperparameters for your dataset in order to build an efficient text classifier. To use autotuning, a researcher inputs the training data as well as a validation set and a time constraint. FastText then uses the allottedtime to
AROMA: USING ML FOR CODE RECOMMENDATION PYTORCH BUILDS THE FUTURE OF AI AND MACHINE LEARNING AT Bridging the research-to-production gap. Historically, AI’s research-to-production pipeline has been tedious and complicated. Multiple steps and tools, fragmented processes, and lack of any clear standardization across the AI industry made it nearly impossible to manage the end-to-end workflow. DETECTRON - FACEBOOK Rapid, flexible research. Detectron was built by Facebook AI Research (FAIR) to support rapid implementation and evaluation of novel computer vision research. It includes implementations for the following object detection algorithms: Detectron can be used out-of-the-box for general object detection or modified to train and run inference on yourFACEBOOK AI PEOPLE
Aparna Lakshmi Ratan is the Director of Product Management for AI Platforms at Facebook. This team works at the intersection of systems and ML to provide an efficient THE FLORES-101 DATA SET: HELPING BUILD BETTER TRANSLATION Today we are open-sourcing FLORES-101, a first-of-its-kind, many-to-many evaluation data set covering 101 languages (10,100 translation directions) from all over the world. DINO AND PAWS: ADVANCING THE STATE OF THE ART IN COMPUTER When pretraining a standard ResNet-50 model with PAWS using just 1 percent of the labels in ImageNet, we get state-of-the-art accuracy while doing 10x fewer pretraining steps. With DINO and PAWS, the AI research community can build new computer vision systems that are far less dependent on labeled data and vast computing resources fortraining.
PYTORCHVIDEO: A DEEP LEARNING LIBRARY FOR VIDEO UNDERSTANDING What it is: PyTorchVideo is a deep learning library for research and applications in video understanding. It provides easy-to-use, efficient, and reproducible implementations of state-of-the-art video models, data sets, transforms, and tools in PyTorch. NOT ALL MEMORIES ARE CREATED EQUAL: LEARNING TO FORGET BY We propose Expire-Span, a method that learns to retain the most important information and expire the irrelevant information. This forgetting of memories enables Transformers to scale to attend over tens of thousands of previous timesteps efficiently, as not all states from previous timesteps are preserved. We demonstrate that Expire-Spancan
FINDINGS OF THE WMT 2019 SHARED TASK ON PARALLEL CORPUS Abstract. Following the WMT 2018 Shared Task on Parallel Corpus Filtering (Koehn et al., 2018), we posed the challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting 2% and 10% of the highest-quality data to be used to train machine translation systems. HOW FACEBOOK ANNOTATES MULTIMODAL TRAINING DATA FOR ML How Facebook annotates multimodal training data for ML. We have built an annotation platform called Halo, which allows Facebook researchers to more easily and efficiently create high-quality training data. Halo creates annotation tasks and then visualizes corresponding data across diverse media types, including images, audio, video, and 3D. COVOST V2: EXPANDING THE LARGEST, MOST DIVERSE CoVoST V2 will facilitate translating 21 languages into English, as well as English into 15 languages. In order to support wider research and applications in multilingual speech translation, we have released CoVoST V2 as free to use via a Creative Commons (CC0) license. Developed in 2019, the initial version of CoVoST used Mozilla’s openResearch
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BRINGING THE WORLD CLOSER TOGETHER BY ADVANCING AIDEEPFAKE DETECTION
Facebook, the Partnership on AI, Microsoft, and academics from Cornell Tech, MIT, University of Oxford, UC Berkeley, University of Maryland, College Park, and University at Albany-SUNY are coming together to build the Deepfake Detection Challenge (DFDC) to catalyze more research and development in this area. BRINGING THE WORLD CLOSER TOGETHER BY ADVANCING AIDENSEPOSE
DensePose establishes dense correspondences between RGB images and a surface-based representation of the human body. To do this, AI researchers built DensePose-COCO, a large-scale, ground-truth dataset with image-to-surface correspondences annotated on 50,000 COCO images. BRINGING THE WORLD CLOSER TOGETHER BY ADVANCING AIGROKNET
GrokNet is a deployed image recognition system for commerce applications that leverages a multi-task learning approach to train a single computer vision trunk. We achieve a 2.1x improvement in exact product match accuracy when compared to the previous state-of-the-art Facebook product recognition system. BRINGING THE WORLD CLOSER TOGETHER BY ADVANCING AIDEEPFAKE DETECTION
Facebook, the Partnership on AI, Microsoft, and academics from Cornell Tech, MIT, University of Oxford, UC Berkeley, University of Maryland, College Park, and University at Albany-SUNY are coming together to build the Deepfake Detection Challenge (DFDC) to catalyze more research and development in this area. BRINGING THE WORLD CLOSER TOGETHER BY ADVANCING AIDENSEPOSE
DensePose establishes dense correspondences between RGB images and a surface-based representation of the human body. To do this, AI researchers built DensePose-COCO, a large-scale, ground-truth dataset with image-to-surface correspondences annotated on 50,000 COCO images. BRINGING THE WORLD CLOSER TOGETHER BY ADVANCING AIGROKNET
GrokNet is a deployed image recognition system for commerce applications that leverages a multi-task learning approach to train a single computer vision trunk. We achieve a 2.1x improvement in exact product match accuracy when compared to the previous state-of-the-art Facebook product recognition system.LATEST NEWS
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PYTORCH BUILDS THE FUTURE OF AI AND MACHINE LEARNING AT FACEBOOKJune 02, 2021
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DYNABOARD: MOVING BEYOND ACCURACY TO HOLISTIC MODEL EVALUATION IN NLPMay 24, 2021
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HIGHLIGHTED PROJECTS USING AI TO CREATE AND SHARE COVID-19 FORECASTS CASUAL CONVERSATIONS DATASET IS NOW AVAILABLE FOR DOWNLOAD LEARN MORE ABOUT KILT BENCHMARKING OPEN-SOURCE AI TOOLS WE SHARE OUR OPEN SOURCE FRAMEWORKS, TOOLS, LIBRARIES, AND MODELS FOR EVERYTHING FROM RESEARCH EXPLORATION TO LARGE-SCALE PRODUCTIONDEPLOYMENT.
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GROKNET: UNIFIED COMPUTER VISION MODEL TRUNK AND EMBEDDINGS FORCOMMERCE
Sean Bell
Yiqun Liu
Sami Alsheikh
Yina Tang...
KDD
ABSTRACT
In this paper, we present GrokNet, a deployed image recognition system for commerce applications. GrokNet leverages a multi-task learning approach to train a single computer vision trunk. We achieve a 2.1x improvement in exact product match accuracy when compared to the previous state-of-the-art Facebook product recognition system.Read the Paper
COMPUTER VISION
LIVE FACE DE-IDENTIFICATION IN VIDEOOran Gafni
Lior Wolf
Yaniv Taigman
International Conference on Computer Vision (ICCV)ABSTRACT
We propose a method for face de-identification that enables fully automatic video modification at high frame rates. The goal is to maximally decorrelate the identity, while having the perception (pose, illumination and expression) fixed.Read the Paper
RESEARCH
SINGLE-NETWORK WHOLE-BODY POSE ESTIMATIONGines Hidalgo
Yaadhav Raaj
Haroon Idrees
Donglai Xiang...
International Conference on Computer Vision (ICCV)ABSTRACT
We present the first single-network approach for 2D whole-body pose estimation, which entails simultaneous localization of body, face, hands, and feet keypoints. Our method maintains constant real-time performance regardless of the number of people in the image. Our approach considerably improves upon OpenPose, the only work so far capable of whole-body pose estimation, both in terms of speed andglobal accuracy.
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SPEECH & AUDIO
A UNIVERSAL MUSIC TRANSLATION NETWORKNoam Mor
Lior Wolf
Adam Polyak
Yaniv Taigman
International Conference on Learning Representations (ICLR)ABSTRACT
We present a method for translating music across musical instruments and styles. This method is based on unsupervised training of a multi-domain wavenet autoencoder, with a shared encoder and a domain-independent latent space that is trained end-to-end onwaveforms.
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LATEST PUBLICATIONS
COMPUTER VISION
GRAPHICS
DEEP RELIGHTABLE APPEARANCE MODELS FOR ANIMATABLE FACES We present a method for building high-fidelity animatable 3D face models that can be posed and rendered with novel lighting environmentsin real-time. …
Sai Bi, Stephen Lombardi,Shunsuke Saito, Tomas Simon, Shih-en Wei, Kevyn McPhail, Ravi Ramamoorthi, Yaser Sheikh, Jason SaragihRead the Paper
CORE MACHINE LEARNINGCOMPUTER VISION
ROBUST AUDIO-VISUAL INSTANCE DISCRIMINATION We present a self-supervised learning method to learn audio and videorepresentations …
Pedro Morgado, Ishan Misra, Nuno VasconcelosRead the Paper
COMPUTER VISION
FAST AND ACCURATE MODEL SCALING In this work we analyze strategies for convolutional neural network scaling; that is, the process of scaling a base convolutional network…
Piotr Dollár, Mannat Singh, Ross GirshickRead the Paper
COMPUTER VISION
GRAPHICS
SINGLE-SHOT FREESTYLE DANCE REENACTMENT The task of motion transfer between a source dancer and a target person is a special case of the pose transfer problem … Oran Gafni, Oron Ashual Lior WolfRead the Paper
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