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nv-tlabs avatar

nv-tlabs/STEAL

0
View on GitHub↗
480 stars·64 forks·Jupyter Notebook·8 viewsnv-tlabs.github.io/STEAL↗

STEAL

STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)

Features

  • Computer Vision Models - Learning semantic boundaries from noisy labels.
  • Robust Learning Frameworks - Learns semantic boundaries from noisy annotations.
  • Video Recognition - Listed in the “Video Recognition” section of the The Incredible Pytorch awesome list.

Star history

Star history chart for nv-tlabs/stealStar history chart for nv-tlabs/steal

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with STEAL

These projects share indexed features with STEAL. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • layumi/seg-uncertaintylayumi avatar

    layumi/Seg-Uncertainty

    394View on GitHub↗

    IJCAI2020 & IJCV2021 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo

    Python
    View on GitHub↗394
  • nvidia/semantic-segmentationNVIDIA avatar

    NVIDIA/semantic-segmentation

    1,823View on GitHub↗

    Nvidia Semantic Segmentation monorepo

    Python
    View on GitHub↗1,823
  • cs230-stanford/cs230-code-examplescs230-stanford avatar

    cs230-stanford/cs230-code-examples

    4,218View on GitHub↗

    This repository provides structured code examples and project templates designed for classroom instruction in machine learning and neural networks. It offers reference implementations of deep learning models for both computer vision and natural language processing tasks, built using PyTorch as the core framework. The codebase is organized as a modular project template with separate directories for data handling, model definitions, and training scripts, promoting reusability and clarity. It includes predefined pipelines for image classification and text processing, along with a command-line in

    Pythoncomputer-visionnatural-language-processingpytorch
    View on GitHub↗4,218
  • aaltovision/dgc-netAaltoVision avatar

    AaltoVision/DGC-Net

    206View on GitHub↗

    A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"

    Jupyter Notebook
    View on GitHub↗206
Compare all 30 related projects→

Frequently asked questions

What does nv-tlabs/steal do?

STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)

What are the main features of nv-tlabs/steal?

The main features of nv-tlabs/steal are: Computer Vision Models, Robust Learning Frameworks, Video Recognition.

Which projects share features with nv-tlabs/steal?

Projects with overlapping indexed features include: nvidia/semantic-segmentation — Nvidia Semantic Segmentation monorepo. layumi/seg-uncertainty — IJCAI2020 & IJCV2021 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo. cs230-stanford/cs230-code-examples — This repository provides structured code examples and project templates designed for classroom instruction in machine… aaltovision/dgc-net — A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network". akshayubhat/deepvideoanalytics. adamian98/pulse — Pulse is a generative model image upscaler and latent space image processor. It functions as a self-supervised photo…