keyu-tian/SparK
[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling" observed · 2026-08-28
Health v2 · maintenance only
22/100
- Activity 0
- Release rhythm 8
- Longevity 95
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1336
- days_rel: n/a
- days_push: 953
- n_releases_24m: 0
Adoption not part of the score
1376 stars · 85 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
SparK is the official PyTorch implementation of an ICLR 2023 Spotlight paper that applies BERT/MAE-style masked image modeling to convolutional networks using sparse convolution and a hierarchical decoder. It can pretrain any CNN (e.g., ResNet, ConvNeXt) in a self-supervised manner without backbone modifications.
Use cases
- pretrain a ResNet or ConvNeXt with masked image modeling
- self-supervised pretraining for CNN backbones
- improve object detection and instance segmentation with pretrained CNN features
- reproduce BERT-style pretraining on convolutional networks
- compare sparse masked modeling against contrastive learning baselines
- fine-tune pretrained CNN weights on ImageNet classification
When to choose
- you want MAE/BERT-style self-supervised pretraining but must use a CNN backbone
- you need better transfer features for detection or segmentation with convolutional models
- you are researching masked image modeling on hierarchical architectures
When to avoid
- you are pretraining vision transformers, where standard MAE applies directly
- you need a maintained production library rather than a research codebase
- you lack GPU resources for large-scale pretraining
Facets
library · maturity stable
machine-learning deep-learning llm-training computer-vision deep-learning image-processing python masked-image-modeling self-supervised-learning sparse-convolution cnn-pretraining bert-style pytorch iclr2023 resnet convnext object-detection gpu linux
6 sources
- readme: https://github.com/keyu-tian/SparK · fetched 2026-08-28 · 378f2b637281
- homepage: https://arxiv.org/abs/2301.03580 · fetched 2026-08-29 · 7b1f2162c48d
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| keyu-tian/SparK | main | 22 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem