Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping

Despite the enormous progress and generalization in robotic grasping in recent years, existing methods have yet to scale and generalize task-oriented grasping to the same extent. This is largely due to the scale of the datasets both in terms of the number of objects and tasks studied… We address these concerns with the TaskGrasp dataset which is more diverse both in terms of objects and tasks, and an order of magnitude larger than previous datasets. The dataset contains 250K task-oriented […]

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Fine-Grained Sentiment Analysis of Smartphone Review

How to conduct fine-grained sentiment analysis: Approaches and Tools Data collection and preparation. For data collection, we scraped the top 100 smartphone reviews from Amazon using python, selenium, and beautifulsoup library. If you don’t know how to use python and beautifulsoup and request a library for web-scraping here is a quick tutorial. Selenium Python bindings provide a simple API to write functional/acceptance tests using Selenium WebDriver. Let’s begin coding    

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Hugging Face – 🤗Hugging Face Newsletter Issue #1 – Aug 20th 2020

News 🤗Welcome to the Hugging Face Newsletter! 🤗 Every few weeks, we’ll be updating you on the latest happenings at Hugging Face. Make sure to subscribe and share with all NLP lovers to get the latest updates on releases, readings, research, and more! Have an idea for the newsletter? Email newsletter@huggingface.co 🚀 Model Hub Highlights 🚀 Open-Source Machine TranslationDid you know that you can translate between many languages with open-source 🤗 Transformers and great models    

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Hugging Face – 🤗Hugging Face Newsletter Issue #2 – Sep 11th 2020

News Transformers gets a new release: v3.1.0 This new version is the first PyPI release to feature: The PEGASUS models, the current State-of-the-Art in summarization DPR, for open-domain Q&A research mBART, a multilingual encoder-decoder model trained using the BART objective Alongside the three new models, we are also releasing a long-awaited feature: “named outputs”. By passing return_dict=True, model outputs can now be accessed as named values as well as by    

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Hugging Face – 🤗Hugging Face Newsletter Issue #3 – Oct 9th 2020

News 📣 Inference API: Pricing Announcement 📣 We’ve just launched our Inference API beta which lets you run fast inference on any of the 3,000+ models made available by the community. It is an optimized and accelerated version of the open-access API that powers our free inference widgets, available on all of our model pages. ➡️ To subscribe, you will need to create or join an organization and head over to

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Hugging Face – 🤗Newsletter Issue #4 – Nov 12th 2020

News Transformers v3.5.0 Model VersioningThe new release of transformers brings a complete rehaul of the weights sharing system, introducing a brand new feature: model versioning, based on the git versioning system and git-lfs, a git-based system for large files. This version introduces the concept of revisions, allowing weights to be accessed with a given identifier: a tag, branch or commit hash identifier. This is accompanied by a rework of the model hub files user interface, showcasing the    

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A Bayesian Nonparametric model for textural pattern heterogeneity

Cancer radiomics is an emerging discipline promising to elucidate lesion phenotypes and tumor heterogeneity through patterns of enhancement, texture, morphology, and shape. The prevailing technique for image texture analysis relies on the construction and synthesis of Gray-Level Co-occurrence Matrices (GLCM)… Practice currently reduces the structured count data of a GLCM to reductive and redundant summary statistics for which analysis requires variable selection and multiple comparisons for each application, thus limiting reproducibility. In this article, we develop a Bayesian multivariate probabilistic […]

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BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data

We describe the BeyondPlanck project in terms of motivation, methodology and main products, and provide a guide to a set of companion papers that describe each result in fuller detail. Building directly on experience from ESA’s Planck mission, we implement a complete end-to-end Bayesian analysis framework for the Planck Low Frequency Instrument (LFI) observations… The primary product is a joint posterior distribution P(omega|d), where omega represents the set of all free instrumental (gain, correlated noise, bandpass etc. ), astrophysical (synchrotron, […]

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Zero-Pair Image to Image Translation using Domain Conditional Normalization

In this paper, we propose an approach based on domain conditional normalization (DCN) for zero-pair image-to-image translation, i.e., translating between two domains which have no paired training data available but each have paired training data with a third domain. We employ a single generator which has an encoder-decoder structure and analyze different implementations of domain conditional normalization to obtain the desired target domain output… The validation benchmark uses RGB-depth pairs and RGB-semantic pairs for training and compares performance for the […]

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Scribble-Supervised Semantic Segmentation by Random Walk on Neural Representation and Self-Supervision on Neural Eigenspa

Scribble-supervised semantic segmentation has gained much attention recently for its promising performance without high-quality annotations. Many approaches have been proposed… Typically, they handle this problem to either introduce a well-labeled dataset from another related task, turn to iterative refinement and post-processing with the graphical model, or manipulate the scribble label. This work aims to achieve semantic segmentation supervised by scribble label directly without auxiliary information and other intermediate manipulation. Specifically, we impose diffusion on neural representation by random walk and […]

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