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BeCarefulOfYournaoke/BPS

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0 stars·0 forks·10 views

BPS

This repo contains PyTorch implementation of Balanced Dataset Distillation via Modeling Multiple Visual Pattern Distribution (BPS, CVPR 2026). BPS produces a pattern-balanced condensed dataset via modeling the multiple visual pattern distribution within each class. This repo contains code for…

Features

  • Decoupled Distillation - Balances distillation by modeling multiple visual pattern distributions.
  • Foundational Research - Balances distillation via modeling multiple visual pattern distributions.

Star history

Star history chart for becarefulofyournaoke/bpsStar history chart for becarefulofyournaoke/bps

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 BPS

These projects share indexed features with BPS. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • angusdujw/diversity-driven-synthesisAngusDujw avatar

    AngusDujw/Diversity-Driven-Synthesis

    8View on GitHub↗

    The sharp increase in data-related expenses has motivated research into condensing datasets while retaining the most informative features. Dataset distillation has thus recently come to the fore. This paradigm generates synthetic datasets that are representative enough to replace the original…

    Python
    View on GitHub↗8
  • brian-moser/prismBrian-Moser avatar

    Brian-Moser/prism

    1View on GitHub↗

    Official PyTorch implementation of paper (TMLR'26) PRISM : Diversifying Dataset Distillation by Decoupling Architectural Priors.

    Python
    View on GitHub↗1
  • dil-iith/direDIL-IITH avatar

    DIL-IITH/DiRe

    1View on GitHub↗

    Code for WACV 2026 paper "DiRe: Diversity-promoting Regularization for Dataset Condensation"

    Python
    View on GitHub↗1
  • andyj1/mdmA

    andyj1/mdm

    0View on GitHub↗

    Official implementation of Multimodal Distribution Matching for Vision-Language Dataset Distillation, a method for condensing a large vision-language dataset into smaller synthetic sets while preserving its downstream performance.

    View on GitHub↗0
Compare all 16 related projects→

Frequently asked questions

What does becarefulofyournaoke/bps do?

This repo contains PyTorch implementation of Balanced Dataset Distillation via Modeling Multiple Visual Pattern Distribution (BPS, CVPR 2026). BPS produces a pattern-balanced condensed dataset via modeling the multiple visual pattern distribution within each class. This repo contains code for…

What are the main features of becarefulofyournaoke/bps?

The main features of becarefulofyournaoke/bps are: Decoupled Distillation, Foundational Research.

Which projects share features with becarefulofyournaoke/bps?

Projects with overlapping indexed features include: angusdujw/diversity-driven-synthesis — The sharp increase in data-related expenses has motivated research into condensing datasets while retaining the most… brian-moser/prism — Official PyTorch implementation of paper (TMLR'26) PRISM : Diversifying Dataset Distillation by Decoupling… dil-iith/dire — Code for WACV 2026 paper "DiRe: Diversity-promoting Regularization for Dataset Condensation". hips/hypergrad — Source code for http://arxiv.org/abs/1502.03492. jiacheng8/cv-dd — Jiacheng Cui, Zhaoyi Li, Xiaochen Ma, Xinyue Bi, Yaxin Luo, Zhiqiang Shen. andyj1/mdm — Official implementation of Multimodal Distribution Matching for Vision-Language Dataset Distillation, a method for…