Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

Code for ALBEF: a new vision-language pre-training method

Open source tools for computational pathology - Nature BME

A curated (most recent) list of resources for Learning with Noisy Labels

Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)

DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image

Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation [Inoue+, CVPR2018].

Single-Stage Semantic Segmentation from Image Labels (CVPR 2020)

Recent weakly supervised semantic segmentation paper

Mask-Free Video Instance Segmentation [CVPR 2023]

Weakly-supervised object detection.

Weakly Supervised Instance Segmentation using Class Peak Response, in CVPR 2018 (Spotlight)

Weakly Supervised Learning for Findings Detection in Medical Images

[EMNLP 2020] Text Classification Using Label Names Only: A Language Model Self-Training Approach

BOND: BERT-Assisted Open-Domain Name Entity Recognition with Distant Supervision

PyTorch implementation of "WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation", CVPR 2017

Scribbles or Points-based weakly-supervised learning for medical image segmentation, a strong baseline, and tutorial for research and application.

[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Caffe codes for our papers "Multiple Instance Detection Network with Online Instance Classifier Refinement" and "PCL: Proposal Cluster Learning for Weakly Supervised Object Detection".